{
  "count": 50,
  "items": [
    {
      "id": 19558,
      "url": "https://www.jmir.org/2026/1/e97536",
      "title": "Health System- and Payer-Level Decision-Making Processes Influencing the Adoption and Sustainability of Patient-Facing Digital Health Tools: Qualitative Study",
      "summary": "Background: Patient-facing digital health tools such as mobile health apps, wearables, and digital therapeutics have expanded rapidly and show promise for improving chronic disease management. Despite increasing evidence of effectiveness, health systems and payers continue to face challenges integrating these tools into routine care. Objective: This study examined the decision-making processes of health system and payer leaders regarding the adoption and sustainability of patient-facing digital",
      "authors": "Mallory Herzog, Linda S Park, Andrew Quanbeck",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-14T21:00:18.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19558"
    },
    {
      "id": 19559,
      "url": "https://www.jmir.org/2026/1/e97672",
      "title": "Predicting Critical Outcomes in Suspected Cardiopulmonary Emergencies Using Dispatch Narratives: Temporal Validation Study",
      "summary": "Background: Early risk stratification in emergency medical services (EMS) is essential for patients presenting with acute cardiopulmonary symptoms, yet prehospital decision-making at the dispatch stage is often based on limited structured information. Free-text dispatch narratives may contain additional clinical signals, but their role in early risk assessment remains insufficiently characterized. Objective: This study aims to develop and temporally validate a natural language processing–assiste",
      "authors": "Zhe Li, Lei Shi, Chunting Luo, Siqi Huang, Jianmin Qin, Min Yao, Sanshan Zhu, Zhengzhuang Huang, Yinghua Nong, Guozheng Qiu, Liwen Lyu",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-14T20:30:13.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19559"
    },
    {
      "id": 19560,
      "url": "https://www.jmir.org/2026/1/e91215",
      "title": "Advancing Evidence-Based Medicine for Population, Intervention, Comparison, and Outcome Element Recognition and Extraction in Medical Literature: Large Language Model Approach",
      "summary": "Background: The exponential expansion of biomedical literature has created an urgent need for efficient methods to recognize and extract population, intervention, comparison, and outcome (PICO) elements—the foundational elements of evidence-based medicine. Objective: This study systematically evaluated 2 complementary approaches for automating PICO recognition and extraction in medical literature: prompt engineering optimization and parameter-efficient fine-tuning (PEFT) of large language models",
      "authors": "Zeyuan Hao, Yifan Duan, Yu Wang",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-14T20:00:19.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19560"
    },
    {
      "id": 19561,
      "url": "https://www.jmir.org/2026/1/e96072",
      "title": "An mHealth Intervention Promoting Physical Activity to Reduce Psychological Distress Among Workers: Randomized Controlled Trial",
      "summary": "Background: Although mobile health (mHealth) interventions serve as potential solutions for addressing mental health problems, evidence on whether mHealth interventions targeting physical activity can reduce psychological distress among generally healthy workers is limited. Objective: This study aimed to investigate the effectiveness of a stand-alone smartphone app, which passively monitors physical activity and psychological distress, in reducing psychological distress among workers. Methods: T",
      "authors": "Kazuhiro Watanabe, Akiomi Inoue, Asuka Sakuraya, Kotaro Imamura, Toru Yoshikawa, Akizumi Tsutsumi",
      "category": "research",
      "topics": "healthcare,finance-investment",
      "published_at": "2026-08-14T19:30:12.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19561"
    },
    {
      "id": 19562,
      "url": "https://www.jmir.org/2026/1/e108878",
      "title": "AI-Powered Robotics Are Personalizing Rehabilitation",
      "summary": null,
      "authors": "Benedette Cuffari",
      "category": "research",
      "topics": "agents-autonomy",
      "published_at": "2026-08-14T16:45:06.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19562"
    },
    {
      "id": 19563,
      "url": "https://www.jmir.org/2026/1/e109041",
      "title": "Beyond Kimi K3: Spillover Effects of Frontier AI Competition on Health Care",
      "summary": null,
      "authors": "Tejas S Athni",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-14T16:45:06.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19563"
    },
    {
      "id": 19250,
      "url": "https://www.jmir.org/2026/1/e93892",
      "title": "Radiomics-Based AI for Predicting Neoadjuvant Immunochemotherapy Pathological Response in Non–Small Cell Lung Cancer: Systematic Review and Meta-Analysis",
      "summary": "Background: Non–small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide. Accurate early prediction of response to neoadjuvant therapy is critical. Objective: We aimed to evaluate the diagnostic performance of radiomics-based AI in predicting pathological complete response (pCR) and major pathological response (MPR) following neoadjuvant immunochemotherapy in NSCLC and to compare it against traditional radiological criteria. Methods: A systematic search of P",
      "authors": "Ziqi Jiang, Yuan Xu, Shuyu Jia, Hongsheng Liu",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-14T04:00:18.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19250"
    },
    {
      "id": 19251,
      "url": "https://www.jmir.org/2026/1/e106648",
      "title": "Digital Decisions: Enhancing Chronic Disease Self-Care Through Digital Health and AI-Enhanced Decision-Making",
      "summary": "Advances in digital health have dramatically changed how patients engage with their health. Rather than relying solely on periodic clinical visits, patients now have access to smartphones, patient portals, wearable devices, and mobile apps that provide support for day-to-day self-care decisions. This commentary discusses the findings of Longhini et al’s systematic review and meta-analysis on the effectiveness of digital health interventions, which found modest improvements in self-care monitorin",
      "authors": "Ashley C Griffin, Donna M Zulman",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-13T21:30:06.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19251"
    },
    {
      "id": 19252,
      "url": "https://www.jmir.org/2026/1/e91820",
      "title": "Digital Health Technology for Improving Physical Function in Adults With Chronic Heart Failure: Systematic Review and Meta-Analysis of Randomized Controlled Trials",
      "summary": "Background: Chronic heart failure (CHF) significantly impairs physical function and quality of life. Although exercise-based cardiac rehabilitation represents a primary therapeutic strategy, participation rates remain low due to logistical barriers. Digital health technologies (DHTs) offer a promising alternative to deliver home-based interventions. However, evidence regarding their specific impact on functional capacity versus daily physical behavior remains inconsistent. Objective: This system",
      "authors": "Zhe Meng, Juncai Li, Jing Yang, Yijia Lin, Qirui Zhang, Longjie Wei, Xiuling Zhou",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-13T20:30:05.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19252"
    },
    {
      "id": 19253,
      "url": "https://www.jmir.org/2026/1/e84378",
      "title": "Exploring Perceptions of Leveraging AI to Improve Outcomes in Maternal, Sexual, and Reproductive Health in Sub-Saharan Africa: Exploratory Qualitative Study",
      "summary": "Background: AI has the potential to transform health care in low- and middle-income countries, where access to quality care remains limited. Maternal, sexual, and reproductive health (MSRH) outcomes are especially poor due to resource shortages, financial barriers, and geographic inequities. With thoughtful implementation, AI could help address these gaps through innovations in diagnostics, health education chatbots, and telemedicine. However, responsible use is essential to ensure AI reduces, r",
      "authors": "Rachel King, Elizabeth Oseku, Cecilia Akatukwasa, Moreen Nanyonjo, Joshua Beinomugisha, Joan Akullo, Jackie Ssemata, Rosalind Parkes-Ratanshi",
      "category": "research",
      "topics": "healthcare,children-education",
      "published_at": "2026-08-13T20:15:11.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19253"
    },
    {
      "id": 19254,
      "url": "https://www.jmir.org/2026/1/e98144",
      "title": "Association Between Daily Food-Tracking Frequency and Clinically Significant Weight Loss: Retrospective Cohort Study of 5132 Mobile App Users",
      "summary": "In this retrospective cohort of 5132 users of a commercial nutrition-tracking mobile application, higher food-tracking frequency was associated with greater weight loss over 6 months; 70.1% (3599/5132) of users lost at least 5% of body weight.",
      "authors": "Sergey Oreshko, Susan Heikkinen",
      "category": "research",
      "topics": "privacy-surveillance",
      "published_at": "2026-08-13T20:00:21.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/19254"
    },
    {
      "id": 18855,
      "url": "https://www.jmir.org/2026/1/e95025",
      "title": "Quantifying the Intensity of Online Social Support via Large Language Model–Based Evidence Extraction: Development and Validation Study",
      "summary": "Background: Online social support, the interaction among individuals in which one helps another during difficult situations through online platforms such as online forums or social media, has proliferated as a vital tool for personal mental health care. Despite the growing usage and importance of online social support, prior studies have mainly focused on either understanding the characteristics of support seekers or merely identifying types of support, which leaves room for improvement in 2 key",
      "authors": "Dahyeon Park, Daejin Choi",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-12T23:15:13.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18855"
    },
    {
      "id": 18856,
      "url": "https://www.jmir.org/2026/1/e90014",
      "title": "Internet Addiction, Mental Health Help-Seeking, and Mental Health Problems Among Chinese Adolescents: Repeated Cross-Sectional Study",
      "summary": "Background: Internet addiction (IA) has been consistently associated with adverse mental health outcomes, but less is known about whether adolescents with IA seek mental health support, and whether associations between help-seeking and mental health problems differ across pathways. Objective: This study aimed to describe mental health help-seeking patterns across internet use and IA status, and examine the independent and interactive associations of IA and help-seeking with mental health problem",
      "authors": "Afei Qin, Meiqi Wang, Lianlong Yu, Suyun Li, Zhaolu Liu, Shoujuan Zheng, Ziming Shao, Cuixia Lv, Long Sun",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-12T23:15:13.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18856"
    },
    {
      "id": 18857,
      "url": "https://www.jmir.org/2026/1/e96824",
      "title": "Public Perception of Health Care Before, During, and After COVID-19: Longitudinal Analysis of Online Reviews",
      "summary": "Background: Online reviews of health care services represent a growing source of unsolicited, citizen-generated data that can complement traditional instruments for monitoring public perception of health systems. However, longitudinal analyses examining how citizens’ perceptions evolved before, during, and after the COVID-19 pandemic remain scarce, and existing studies have rarely differentiated between levels of care. Objective: This study aimed to examine the longitudinal evolution of public p",
      "authors": "Javier Gazquez-Garcia, Carlos Luis Sánchez-Bocanegra, Carlos Fernandez-Llatas",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-12T19:30:16.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18857"
    },
    {
      "id": 18858,
      "url": "https://www.jmir.org/2026/1/e92184",
      "title": "Effects of Digital Health Interventions on Breastfeeding Rates, Self-Efficacy, and Knowledge: Systematic Review and Meta-Analysis",
      "summary": "Background: The current global status of breastfeeding is marked by both progress and challenges. Digital health interventions (DHIs) have emerged as a promising strategy for improving breastfeeding practices, yet evidence regarding their impact on breastfeeding outcomes remains limited. Objective: This study aimed to evaluate the impact of DHIs on breastfeeding practices and outcomes. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we s",
      "authors": "Jiahe Sun, Yu Wang, Shuang Hu, Yajie Ding, Congshan Pu, Danni Song, Jiaai Xia, Chunjian Shan",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-12T19:00:19.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18858"
    },
    {
      "id": 18484,
      "url": "https://www.jmir.org/2026/1/e98026",
      "title": "Critical Care–Specific vs General-Purpose Large Language Models in Emergency Intensive Care Unit Diagnosis: Single-Center Retrospective Paired Comparative Study",
      "summary": "Background: The emergency intensive care unit (EICU) manages the most critically ill patients, where rapid and accurate diagnosis is essential yet challenging. Diagnostic error rates in this setting are more than twice as high as in general wards, with serious consequences for patient outcomes. Large language models (LLMs) have attracted growing interest as decision-support tools; however, direct comparative evidence between critical care–specialized and general-purpose LLMs across the admission",
      "authors": "Lihong Zheng, Zeyu Lin, Xiaolu Liu, Zhao Fan, Zhong He, Junjie Xu, Lu Yin",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-11T21:31:19.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18484"
    },
    {
      "id": 18485,
      "url": "https://www.jmir.org/2026/1/e92813",
      "title": "Social Media Influencer Marketing as a Clinical Trial Recruitment Modality: Tutorial Informed by One Study’s Approach",
      "summary": "Background: Influencer marketing (paid promotion by individuals with large, engaged social media followings) has become a major commercial advertising strategy, projected to reach US $32 billion globally in 2025. Clinical trials increasingly recruit through digital channels such as social media advertisements and patient portal messages. However, to our knowledge, influencer marketing has not been described as a clinical trial recruitment modality, and no practical guidance exists for investigat",
      "authors": "Timothy B Plante, Jingyi Cao, Tamunotonye Harry, Yuanyuan Feng, Azuka Amaka Ngige, Hailey N Miller, Kayla Ferro, Marian E B Budu, Stephen P Juraschek",
      "category": "research",
      "topics": "healthcare,finance-investment,biotech",
      "published_at": "2026-08-11T21:00:23.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18485"
    },
    {
      "id": 18486,
      "url": "https://www.jmir.org/2026/1/e92842",
      "title": "Prioritizing Equity in Design and Implementation of Consumer-Facing Digital Resources to Support Engagement and Shared Decision-Making",
      "summary": "A digitally enabled health system offers the opportunity to address gaps in the implementation of shared decision-making, a collaborative process between health professionals and consumers to decide on the best test, treatment, or management option based on clinical evidence and the consumer’s values and informed preferences. There is increasing design and availability of digital tools online to support shared decision-making. Providing opportunities for all consumers to make shared health care",
      "authors": "Jenna Smith, Julie Ayre, Carissa Bonner, Danielle Muscat, Heather L Shepherd, Eva Hussain, Husna Amani, Marguerite Tracy, Kristie R Weir, Kathleen McFadden, Kirsten J McCaffery, Jolyn Hersch",
      "category": "research",
      "topics": "bias-fairness,healthcare",
      "published_at": "2026-08-11T21:00:23.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18486"
    },
    {
      "id": 18487,
      "url": "https://www.jmir.org/2026/1/e73364",
      "title": "A Machine Learning Pipeline to Analyze Global Sentiment and Factors Influencing Retinoblastoma Treatment Hesitancy: Observational Infodemiology Study",
      "summary": "Background: The use of social media in cancer research, patient support, and information sharing has been well documented. Objective: Using retinoblastoma as a model, we use the information provided from Twitter (subsequently rebranded X) to understand patients’ treatment-seeking behavior and barriers, as well as investigate its application in research and epidemiology for rare diseases. Methods: Posts on retinoblastoma were extracted from Twitter. We trained BERT (Bidirectional Encoder Represen",
      "authors": "Emily S Wong, Richard W Choy, Esther W Tang, Yuzhou Zhang, Xiu Juan Zhang, Linbin Zhou, Wai Kit Chu, Li Jia Chen, Clement C Tham, Chi Pui Pang, Jason C Yam",
      "category": "research",
      "topics": "healthcare,finance-investment",
      "published_at": "2026-08-11T19:30:15.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18487"
    },
    {
      "id": 18488,
      "url": "https://www.jmir.org/2026/1/e86679",
      "title": "Internet Attachment–Based Compassion Therapy for Adults With Chronic Medical Conditions: Randomized Controlled Trial",
      "summary": "Background: Chronic medical illnesses coexist with mental health challenges, negatively impacting quality of life and well-being. Compassion-based interventions have shown promise for individuals with chronic conditions, yet accessibility barriers limit their implementation. Internet-delivered formats may address these limitations while maintaining effectiveness. To our knowledge, no fully self-guided, internet-delivered attachment-based compassion intervention has been tested in a transdiagnost",
      "authors": "Rocío Herrero, Marian Martínez-Sanchis, Ángel Zamora, María Dolores Vara, Daniel Campos, Javier García-Campayo, Rosa Baños",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-11T17:00:23.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18488"
    },
    {
      "id": 18489,
      "url": "https://www.jmir.org/2026/1/e92374",
      "title": "Finite State Machine–Guided Retrieval-Augmented Generation Improves Expert-Rated Acceptability of a Peripherally Inserted Central Catheter Self-Management Chatbot: Single-Center Content Validation Study",
      "summary": "Background: Patients with cancer undergoing long-term or vesicant chemotherapy frequently require peripherally inserted central catheters (PICCs). Due to the nature of ambulatory treatment administration, self-PICC management is essential for the continuation and completion of the planned treatment. Large language models offer potential for continuous patient support, but hallucinations and insufficient adherence to clinical protocols remain concerns. Fine-tuning (FT) and retrieval-augmented gen",
      "authors": "Mangyeong Lee, Seung-Beom Cho, Jae-Wook Yu, Junghee Yoon, Jae-Boong Choi, Kyu-Hwan Jung, Juhee Cho",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-11T16:30:14.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18489"
    },
    {
      "id": 18081,
      "url": "https://www.jmir.org/2026/1/e88971",
      "title": "Effects of Digital Interventions on Symptom Improvement and Quality of Life in Patients With Overactive Bladder: Systematic Review and Meta-Analysis",
      "summary": "Background: Overactive bladder (OAB) is a prevalent condition that substantially impairs quality of life (QoL); however, the real-world utility of standard behavioral and pharmacological therapies is often limited by poor long-term adherence. Digital interventions have emerged as a promising strategy to provide accessible and personalized support, but their overall efficacy compared with conventional care remains to be systematically established. Objective: This study aimed to evaluate the effic",
      "authors": "Ni Wang, Fan Fan, Yuan Ou, Shanhe Huang, Chigang Cao, Hai Huang, Hao Huang",
      "category": "research",
      "topics": "biotech",
      "published_at": "2026-08-10T22:00:34.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18081"
    },
    {
      "id": 18082,
      "url": "https://www.jmir.org/2026/1/e89124",
      "title": "Attrition in Digital Self-Management Interventions for Patients With Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD): Mixed Methods Systematic Review",
      "summary": "Background: Lifestyle modification delivered through digital self-management is central to metabolic dysfunction-associated steatotic liver disease (MASLD) care, yet long-term engagement remains the threshold beyond which clinical benefit is realized. Understanding attrition requires examining both retention (dropout) and adherence (usage quality), which are often evaluated in isolation. Existing systematic reviews of digital interventions for MASLD have focused predominantly on clinical effecti",
      "authors": "Rui Pang, Yihong Xu, Xiaoxiao Yu, Jianan Wang, Zhichao Yang, Haofen Li, Xiaojie Zhang, Ning Chen, Xiao Liang, Hongying Pan",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-10T21:15:03.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18082"
    },
    {
      "id": 18083,
      "url": "https://www.jmir.org/2026/1/e58233",
      "title": "Automated Features, Algorithms, and Technologies of Electronic Early Warning/Track-and-Trigger Systems: Systematic Review",
      "summary": "Background: Electronic early warning/track-and-trigger systems (EW/TTS) are crucial for patient monitoring, detecting clinical deterioration (CD), and activating rapid response teams. Understanding the current level of automation in EW/TTS is essential. Objective: This study aimed to provide a comprehensive overview and critical assessment of electronic EW/TTS, including automated features, algorithms, and technologies, following a published registered study protocol. Methods: Based on the PRISM",
      "authors": "Sharareh Rostam Niakan Kalhori, Mostafa Haghi, Masresha Derese Tegegne, Viktor MG Sobotta, Paulo Haas, Nagarajan Ganapathy, Thomas M Deserno",
      "category": "research",
      "topics": "jobs-economy,healthcare",
      "published_at": "2026-08-10T21:00:24.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18083"
    },
    {
      "id": 18084,
      "url": "https://www.jmir.org/2026/1/e95678",
      "title": "Social Media as a Driver of Obesity in Children and Adolescents (Aged 6-18 Years): It Is Time for Regulatory Action",
      "summary": "Obesity in children and adolescents is rising in China and globally, with health consequences that are already evident during childhood. This Viewpoint represents the authors’ interpretation of current evidence and policy experience, using China as an illustrative case for a wider international challenge. We argue that social media should be considered a modifiable obesogenic environment because it can amplify sedentary behavior, digital food marketing, disrupted sleep, body image pressures, cyb",
      "authors": "Yuwei Liu, Wenyun Li, Li Ming Wen, Gengsheng He",
      "category": "research",
      "topics": "regulation,healthcare,children-education,environment",
      "published_at": "2026-08-10T21:00:24.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18084"
    },
    {
      "id": 18085,
      "url": "https://www.jmir.org/2026/1/e74150",
      "title": "Building a Natural Language Processing Augmented Information Support System to Enhance Supportive Care for Patients With Prostate Cancer and Families: User-Centered, Iterative Approach",
      "summary": "Background: Patients with prostate cancer and their families face significant challenges during transitions from diagnosis to treatment and posttreatment self-management, particularly in accessing, understanding, and using complex health information. Objective: We aimed to develop the Interactive Prostate Cancer Information, Communication, and Support Program (iPICS), a natural language processing (NLP)–augmented eHealth platform designed to enhance care continuity, support decision-making, and",
      "authors": "Lixin Song, Xiaomeng Wang, Fei Yu, Dongmei Zuo, Lisa Hart Ranzinger, Michael Liss, Hung-Jui Tan",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-10T19:30:06.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18085"
    },
    {
      "id": 18086,
      "url": "https://www.jmir.org/2026/1/e89858",
      "title": "Comparative Performance of AI Models and Clinicians in Evidence-Based Cardiovascular Disease Management for People Living With HIV: Comparative Study",
      "summary": "Background: Although widespread antiretroviral therapy has extended the life expectancy of people living with HIV, cardiovascular disease (CVD) has emerged as a primary comorbidity. Persistent cross-specialty knowledge gaps in routine clinical practice lead to suboptimal adherence to guidelines. Integrated, evidence-based tools are urgently needed to overcome these interdisciplinary barriers. While large language models (LLMs) have demonstrated significant capabilities in medicine, no systematic",
      "authors": "Tianqi Kong, Liqin Sun, Yinsong Luo, Xi Xiao, Jin Li, Jiaye Liu",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-10T19:15:11.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18086"
    },
    {
      "id": 18087,
      "url": "https://www.jmir.org/2026/1/e84086",
      "title": "Intelligent Framework for Adverse Drug Event Identification Using Large Language Models and Retrieval-Augmented Generation: Development and Evaluation Study",
      "summary": "Background: Adverse drug events (ADEs) pose significant public health challenges and economic burdens. While substantial ADE information is documented in unstructured clinical notes, its extraction remains difficult due to semantic complexity. Large language models (LLMs) offer promising text comprehension capabilities but are often hindered by domain-specific hallucinations. Objective: This study aims to evaluate the effectiveness of retrieval-augmented generation (RAG) in improving the identif",
      "authors": "Junlong Ma, Xuehong Wu, Zeying Feng, Yun Kuang, Zhendong Ding, Min Li, Guoping Yang",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-10T18:30:15.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18087"
    },
    {
      "id": 18088,
      "url": "https://www.jmir.org/2026/1/e86467",
      "title": "Using Natural Language Processing to Identify Adverse Drug Events Characterized by Medication Replacement in Primary Care Electronic Medical Records: Algorithm and Validation Study",
      "summary": "Background: Health care systems generate vast amounts of unstructured text, such as clinical notes, which capture nuanced patient experiences, clinical reasoning, and subtle indicators of health status. While health system research has traditionally relied upon structured data, natural language processing (NLP) enables the extraction of this rich textual information. Leveraging NLP could improve the identification and characterization of underreported adverse drug events (ADEs). Objective: The p",
      "authors": "Alan Katz, Abhishek Dhankar, Gillian Fransoo, Diane Gordon Pappas, Amani F Hamad, Christine Leong, Alexander Singer",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-10T17:30:10.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18088"
    },
    {
      "id": 18089,
      "url": "https://www.jmir.org/2026/1/e87514",
      "title": "Designing for Autonomous Motivation: Qualitative Interview Study on Pre-Enrollment Preferences of Survivors of Cancer for Digital Health Behavior Change Programs",
      "summary": "Background: Despite elevated recurrence risks associated with modifiable lifestyle factors, many survivors of cancer do not adhere to health promotion recommendations. Digital health interventions hold promise for supporting behavior change, but few studies involve survivors in intervention design, potentially limiting real-world effectiveness. Understanding the preferences and support needs of survivors of cancer is crucial for developing effective digital health behavior change interventions.",
      "authors": "Monisola Jayeoba, Rachel Sohn, Abigail Louise Weiss, Anja Stanic, Rana Mazzetta, Alice Pham, Laura Danielle Scanlan, Mario Garcia, Armaan Sidhu, Elizabeth Ho, Sofia F Garcia, Brian Hitsman, Siobhan M Phillips, Bonnie Spring, Maia Jacobs",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-10T17:00:21.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/18089"
    },
    {
      "id": 17500,
      "url": "https://www.jmir.org/2026/1/e94837",
      "title": "Development and Validation of an Interpretable Machine Learning Model for Staging Helicobacter pylori–Initiated Intestinal-Type Gastric Cancer in the Correa Cascade: Cross-Sectional Study",
      "summary": "Background: Gastric cancer (GC) is one of the most common malignant tumors worldwide, with –associated intestinal-type gastric cancer (IGC) being the most prevalent subtype, accounting for approximately 85% of cases. Because most patients are diagnosed at intermediate or advanced stages, early screening and accurate stage stratification of IGC progression remain major clinical challenges. Objective: This study aimed to develop an interpretable machine learning (ML) model that leverages routine l",
      "authors": "Jiawei Tang, Huijin Chen, Wenwen Zhang, Alfred Chin Yen Tay, Barry J Marshall, Cong Ma, Liang Wang",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-07T23:00:08.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17500"
    },
    {
      "id": 17501,
      "url": "https://www.jmir.org/2026/1/e84454",
      "title": "Machine Learning to Identify Point-of-Care Ultrasound and Evaluate Standardized Documentation: Retrospective Operational Cohort Study",
      "summary": "Background: Point-of-care ultrasound (POCUS) is integral to obstetrics and gynecology (OBGYN), offering bedside diagnostic and therapeutic advantages. Despite its widespread adoption, accurate documentation and billing remain challenging due to inconsistent workflows, variable free-text note quality, and inefficiencies within electronic health record (EHR) systems. These barriers often result in missed procedural charges and hinder operational, educational, and reimbursement efforts. Objective:",
      "authors": "Kevin Nguyen, Zewen Wu, Chu-An Tsai, John Vandervest, D’Anna Lammers, Ruth Cassidy, Zachary Murphy, Balaji Pandian, Maya M Hammoud, Jennifer Collin, Roger Smith, Rosalyn Maben-Feaster, Amy Kaufman Eddy, Michael L Burns",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-07T21:45:03.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17501"
    },
    {
      "id": 17502,
      "url": "https://www.jmir.org/2026/1/e96187",
      "title": "Heterogeneous Associations Between Frequent Virtual Communication and Loneliness Among Older Adults: Observational Analysis",
      "summary": "Background: Loneliness is a long-standing and widely acknowledged public health problem among older adults, yet evidence remains mixed regarding how virtual communication is associated with loneliness. Less is known about whether this association varies across baseline profiles among older adults. Objective: This study aimed to examine the association between frequent virtual communication with family, friends, or acquaintances and loneliness among older adults in Japan and explore whether this",
      "authors": "Daisuke Kato, Ichiro Kawachi, Katsunori Kondo, Atsushi Nakagomi, Koichiro Shiba",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-07T21:30:40.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17502"
    },
    {
      "id": 17503,
      "url": "https://www.jmir.org/2026/1/e84887",
      "title": "Clinician Participation in Innovation Labs at University Hospitals: Mixed Methods Study",
      "summary": "Background: Innovation labs (ILs) are increasingly being implemented in hospital settings to propel collaboration and experimentation against the backdrop of digital transformation. While these labs offer substantial potential for accelerating the development and testing of novel clinical and operational solutions, the sustainable participation of hospital staff remains a challenge. Frontline clinicians and nurses possess essential contextual knowledge yet face significant structural, cultural,",
      "authors": "Louis Agha-Mir-Salim, Thorsten Adami, Anne Rike Flint, Anette Ströh, Felix Balzer, Akira-Sebastian Poncette",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-07T21:30:03.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17503"
    },
    {
      "id": 17504,
      "url": "https://www.jmir.org/2026/1/e96800",
      "title": "Effectiveness of Socially Assistive Robots in Promoting Positive Emotional Responses and Alleviating Postoperative Pain Among Children: Quantitative Study",
      "summary": "Background: Pain remains a critical issue among hospitalized children and may negatively affect postoperative recovery. In addition to pharmacological pain management, nonpharmacological approaches have been used to support pediatric care. Among these emerging approaches, socially assistive robots (SARs) may offer an opportunity to support children during hospitalization. However, limited evidence exists regarding the use of SARs in pediatric postoperative recovery and their influence on childre",
      "authors": "Fang-Yu Hsu, Yun-Hsuan Lee, Chih-Yuan Yang, Sue-hsien Chen, Shih-Ming Chu, Angela Shin-Yu Lien",
      "category": "research",
      "topics": "children-education,agents-autonomy,biotech",
      "published_at": "2026-08-07T21:00:05.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17504"
    },
    {
      "id": 17505,
      "url": "https://www.jmir.org/2026/1/e100442",
      "title": "Conversational Large Language Models for Vestibular Diagnosis in Outpatient Clinics: Prospective Multicenter Diagnostic Accuracy Study",
      "summary": "Background: Vestibular disorders are common, burdensome, and frequently misdiagnosed, particularly in nonspecialist settings where history-taking is often incomplete or inconsistently structured. Digital health tools that standardize symptom elicitation could improve diagnostic triage, but most existing systems rely on static questionnaires or rule-based logic. Large language models (LLMs) offer a more flexible alternative through adaptive, natural-language consultations, but prospective evidenc",
      "authors": "Chongkai Lu, Ruiqi Zhang, Huaili Jiang, Yanping Yu, Sulin Zhang, Qin Lin, Peixia Wu, Huawei Li",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-07T20:30:12.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17505"
    },
    {
      "id": 17506,
      "url": "https://www.jmir.org/2026/1/e92183",
      "title": "A Bilingual Benchmark for Evaluating Diagnostic Performance of Multimodal Large Language Models in Radiology (RadM-Bench): Evaluation Development and Validation",
      "summary": "Background: Multimodal large language models are increasingly used in radiological diagnosis, but their performance has not been systematically evaluated across volumetric (3D) imaging, real-world clinical versus public teaching cases, and bilingual contexts. Objective: The aim of the study is to develop a bilingual radiology benchmark and characterize the diagnostic performance of state-of-the-art multimodal large language models across input modality, clinical setting (public teaching vs routi",
      "authors": "Qingxia Wu, Qingxia Wu, Peipei Zhang, Zhifeng Yi, Yu Shen, Yan Bai, Hongna Tan, Pei Dong, Zhong Xue, Neil Roberts, Meiyun Wang",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-07T20:15:11.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17506"
    },
    {
      "id": 17152,
      "url": "https://www.jmir.org/2026/1/e85281",
      "title": "Avatar-Mediated Telepsychotherapy in a Metaverse-Informed Virtual Environment: Qualitative Study of User Experiences and Design Requirements",
      "summary": "Background: Face-to-face psychotherapy remains the gold standard for mental health treatment; however, it faces accessibility barriers, including geographical constraints, costs, and stigma. Although videoconferencing psychotherapy addresses some limitations, challenges with engagement and therapeutic alliance persist. Avatar-mediated telepsychotherapy (AMT) in a metaverse-informed virtual environment has been proposed as a possible extension of digitally delivered mental health care, combining",
      "authors": "Hyeri Lee, Ji-Hyun Hwang, Chul-Hyun Cho, Jeongyun Heo",
      "category": "research",
      "topics": "healthcare,environment",
      "published_at": "2026-08-06T21:00:22.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17152"
    },
    {
      "id": 17153,
      "url": "https://www.jmir.org/2026/1/e90502",
      "title": "AI-Based Phenotyping of Atrial Fibrillation Through Generative Topographic Mapping: Prospective Murcia Atrial Fibrillation Project III Cohort Study",
      "summary": "Background: The clinical heterogeneity of atrial fibrillation (AF) challenges current classifications and risk scores, limiting their real-world applicability. AI-driven methods may enhance phenotyping and risk stratification. Objective: This study aimed to apply a generative topographic mapping (GTM)–based clustering approach to a large, real-world, prospective AF cohort to identify clinically relevant phenotypes and assess their associations with clinical outcomes. Methods: We conducted a pros",
      "authors": "Eva Soler Espejo, Yang Chen, María Pilar Ramos-Bratos, Sandra Ortega-Martorell, Iván Olier, José Miguel Rivera-Caravaca, Francisco Marín, Vanessa Roldán, Gregory Y.H. Lip",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-06T21:00:19.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17153"
    },
    {
      "id": 17154,
      "url": "https://www.jmir.org/2026/1/e89963",
      "title": "Stepwise Diagnostic Evaluation of Chinese Large Language Models: Comparative Study of Common and Rare Diseases",
      "summary": "Background: Large language models (LLMs) are increasingly applied in clinical decision support, yet their diagnostic performance in Chinese-language settings and under realistic clinical workflows remains unclear. In particular, how LLMs perform across diseases with different prevalence and under stepwise diagnostic processes has not been well characterized. Objective: This study aimed to evaluate the diagnostic capabilities of LLMs for common diseases and rare diseases using clinical vignettes",
      "authors": "Jiayi Wang, Jiao Yang, Rui Guo",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-06T20:30:11.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17154"
    },
    {
      "id": 17155,
      "url": "https://www.jmir.org/2026/1/e90339",
      "title": "Use of Information and Communication Technologies in Patients With Cancer Receiving Antineoplastic or Supportive Therapy: Comparative Cross-Sectional Survey",
      "summary": "Background: The expansion of information and communication technologies (ICTs) has transformed the way patients access health information and manage their disease. In oncology and hematology care, the use of digital tools and mobile health has increased, especially after the COVID-19 pandemic, although challenges remain regarding adoption, trust, and perceived utility. Objective: This study aimed to evaluate the current use of ICTs by patients with cancer receiving antineoplastic and/or supporti",
      "authors": "Roberto Collado-Borrell, Vicente Escudero-Vilaplana, Antonio Prieto-Romero, Andres Jesus Muñoz Martin, Marta Cantero-Martín, Cristina Villanueva-Bueno, Jose Luis Revuelta-Herrero, Ana Herranz-Alonso, Maria Sanjurjo-Saez",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-06T20:30:11.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17155"
    },
    {
      "id": 17156,
      "url": "https://www.jmir.org/2026/1/e93861",
      "title": "The Digital Evolution of the Medical Black Bag: Environmental Scan With Trend Analysis and Horizon Scanning",
      "summary": "Background: The medical black bag is synonymous with physicians, especially general practitioners, who are expected to be ready to provide care across settings. The content of the devices they use will likely expand due to the proliferation of digital tools. As portable diagnostics diversify, guidance is increasingly needed on which tools clinicians should choose and what this shift may mean for the physical examination and point-of-care assessment. Objective: This study aimed to map the current",
      "authors": "Gellért Katonai, Nora Arvai, Bertalan Mesko",
      "category": "research",
      "topics": "healthcare,environment",
      "published_at": "2026-08-06T20:30:11.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/17156"
    },
    {
      "id": 16726,
      "url": "https://www.jmir.org/2026/1/e94017",
      "title": "Symptom Tracking for Patient-Reported Outcomes in Cancer: User-Centered Design of the AthenaCompanion Web Application",
      "summary": "Background: Routine monitoring of patient-reported outcomes (PROs) during cancer treatment improves symptom control and quality of life, yet real-world uptake and sustained engagement with PRO monitoring remain suboptimal. Gamification has been shown to improve engagement with digital health interventions. User-centered design approaches are needed to ensure that gamified PRO tools are acceptable, usable, and responsive to patient and clinician needs, especially for older adult users. Objective:",
      "authors": "Kyle Nolla, Laura M Perry, Anvitha Gogineni, Sheetal Kircher, Nisha Mohindra, Michael Bass, Macy K Tetrick, Gabriela Sanchez-Petitto, Anne Noonan, Carolyn Presley, David Cella, Roberto M Benzo",
      "category": "research",
      "topics": "privacy-surveillance,healthcare",
      "published_at": "2026-08-05T20:45:10.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/16726"
    },
    {
      "id": 16727,
      "url": "https://www.jmir.org/2026/1/e89179",
      "title": "Digital Health Communication Engagement Experiences of Older Adults in Community Contexts: Qualitative Systematic Review and Meta-Ethnography",
      "summary": "Background: The global population is aging rapidly, straining health care and social systems. Amid digital transformation, older adults face pronounced obstacles to participating in and benefiting from health communication. Prior syntheses emphasized technology adoption or clinical effectiveness, and health communication reviews focused on formal or home-based care. How older adults experience digital health communication as an everyday, relational process in community contexts and how trust and",
      "authors": "Xinxin Wang, Jianying Zhou, Kari Aerzuguli, Yufei Xing, Wei Luan, Qiong Fang",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-05T20:45:10.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/16727"
    },
    {
      "id": 16728,
      "url": "https://www.jmir.org/2026/1/e89177",
      "title": "Comparing Video-Based and Face-to-Face Psychotherapy: Systematic Review and Multilevel Meta-Analysis Across Mental Disorders",
      "summary": "Background: Video-based psychotherapy (VBT) is increasingly used to expand access to mental health care. Review studies generally report symptom outcomes similar to those achieved with face-to-face (F2F) psychotherapy. However, these studies often analyze VBT alongside other remote modalities, and it remains unclear what portion of the effects can be attributed to the video-based setting itself. Objective: The objective of this systematic review is to compare VBT and F2F psychotherapy in terms o",
      "authors": "Christian Meyer-Keirath, Hannah Wallis, Mariebelle Kaus, Michael Schenk, Jolina Holzhaus, Caroline Rometsch, Claudia Buntrock, Christian Apfelbacher, Florian Junne",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-05T19:00:19.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/16728"
    },
    {
      "id": 16358,
      "url": "https://www.jmir.org/2026/1/e91807",
      "title": "Digital Gaze and Vicarious Trauma Among Intensive Care Unit Nurses in Alarm-Monitoring Ecologies: Qualitative Interview Study",
      "summary": "Background: Intensive care units (ICUs) rely on continuous physiological monitoring and frequent alarms to detect patient deterioration. Although alarm fatigue has been widely discussed as a patient safety and workflow issue, less is known about how monitoring systems shape nurses’ attention, visibility, perceived accountability, emotional strain, and recovery after distressing events. Understanding these experiences is important for designing safer monitoring displays, alarm behavior, communica",
      "authors": "Yuanyuan Wang, Hongyu Chen, Kui Fang, Xu Guo, Yueqin Gu",
      "category": "research",
      "topics": "healthcare,transparency",
      "published_at": "2026-08-04T20:15:12.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/16358"
    },
    {
      "id": 16359,
      "url": "https://www.jmir.org/2026/1/e92373",
      "title": "The Scale for AI Literacy in Health Care Workers: Development and Validation",
      "summary": "Background: AI is increasingly embedded in health care systems; yet, validated instruments for assessing AI literacy among health care workers remain limited. Existing measures are often designed for students or general populations and may not adequately reflect competencies required in health care practice. Objective: This study aimed to develop and validate the Scale for AI Literacy in Health Care Workers (SAIL-HCW), a new instrument designed to assess AI literacy across domains relevant to he",
      "authors": "Chin-Siang Ang, Sakura Ito, Saumya Bajaj, Minyang Chow, Jennifer Cleland, Jonty Heaversedge",
      "category": "research",
      "topics": "healthcare,children-education",
      "published_at": "2026-08-04T19:30:16.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/16359"
    },
    {
      "id": 16360,
      "url": "https://www.jmir.org/2026/1/e93618",
      "title": "Cognitive Workload and Mental Burden in Health Care Professionals Interacting With AI: Systematic Review and Meta-Analysis",
      "summary": "Background: AI adoption in health care has accelerated rapidly, with ambient documentation tools, diagnostic imaging AI, and clinical decision support systems (CDSSs) entering routine practice. However, the cognitive demands placed on clinicians supervising these systems remain understudied. Specifically, the concept of verification burden requires closer examination. Consequently, institutional decision-makers lack a structured, certainty-graded evidence base regarding the true impact of AI on",
      "authors": "Eun Jeong Gong, Chang Seok Bang, Jae Jun Lee",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-04T14:00:24.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/16360"
    },
    {
      "id": 15940,
      "url": "https://www.jmir.org/2026/1/e90046",
      "title": "Evaluation Methods for Inference-Time Retrieval-Augmented and Graph Retrieval-Augmented Large Language Models in Health Care: Scoping Review",
      "summary": "Background: Inference-time retrieval augmentation is increasingly used to improve the traceability and verifiability of large language model (LLM) applications in health care. Evaluation practices for text-based retrieval-augmented generation (RAG) and graph-structured RAG (GraphRAG) systems remain heterogeneous, which limits comparison across studies and complicates judgments about clinical readiness. Objective: This review mapped evaluation methods for inference-time retrieval-augmented and gr",
      "authors": "Yuhan Zhao, Yiqun Miao, Rongrong Guo, Yuan Luo, Huiying Wang, Ying Wu",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-08-03T20:00:27.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/15940"
    },
    {
      "id": 15405,
      "url": "https://www.jmir.org/2026/1/e97772",
      "title": "Social Media Discourse on Breast Cancer Screening Barriers in Japanese and English: Cross-Sectional Infodemiology Study",
      "summary": "Background: Despite clinical advances, breast cancer screening adherence remains stagnant in Japan ( 70%). Understanding distinct cross-cultural barriers is essential; however, traditional methodologies often fail to capture visceral, real-world individual experiences and hidden deterrents to screening. Objective: This study aims to characterize and compare cross-cultural informatics profiles of barriers to breast cancer screening across Japanese-language and English-language social media discou",
      "authors": "Mitsuo Terada, Rie Kawabori Tahara, Yumi Wanifuchi-Endo, Tomoko Asano, Nanae Horisawa, Kazuki Nozawa, Ayaka Isogai, Nari Kureyama, Hikaru Kawahara, Mika Kotani, Yuya Tanaka, Marie Mizumoto, Atsushi Fushimi, Nami Yamashita, Madoka Iwase, Asumi Iesato, Tatsuya Toyama",
      "category": "research",
      "topics": "healthcare",
      "published_at": "2026-07-31T20:00:04.000Z",
      "source": "JMIR (Journal of Medical Internet Research)",
      "ethics_ai_record_url": "https://ethics.ai/record/15405"
    }
  ],
  "attribution": "via ethics.ai"
}