Healthcare

Last May, EFF reported that a sheriff’s office in Texas searched data from more than 83,000 automated license plate reader (ALPR) cameras to track down a woman suspected of self-managing an abortion. ALPRs are promoted as tools for keeping communities safe by finding missing persons and locating stolen vehicles, but this case showed how ALPRS can be weaponized to investigate people’s private healthcare decisions. And these aren’t the only tools in the surveillance arsenal: others include locatio

Recent progress in 3D human pose estimation has made markerless recovery of skeletal motion increasingly accurate and scalable. However, most pose estimators remain optimized for geometric keypoint accuracy, while many real-world applications in rehabilitation, sports science, ergonomics, and clinical movement analysis require biomechanical quantities that describe how the body moves, loads, and activates. In this work, we propose BioModule, a lightweight plug-in temporal transformer that attach

AI-Enabled Citiverse: Use Cases for Cities in the Age of AI – Public Safety, Health and Disaster Resilience Artificial intelligence (AI) Digital transformation Smart cities Digital twins Internet of ...

Hepatocellular carcinoma (HCC) is a common malignancy and a leading cause of cancer-related mortality. Current guidelines and staging systems provide coarse categories, but often miss within-stage heterogeneity and the clinical context in electronic medical records (EMRs). We present HCC-STAR (Hepatocellular Carcinoma Staging, Treatment And pRognosis), a clinically aligned large language model that reads routine EMR narratives and jointly outputs risk score-based staging, ranked guideline-consis

Enterprise artificial intelligence infrastructure startup Mindbeam AI Inc. today published research showing how generative AI can aid in the discovery of safer pain-relief drugs. The company used acetaminophen, one of the most widely used over-the-counter pain relievers worldwide, as a starting point. Using a combination of generative AI, computational modeling and virtual screening, the Mindbeam […] The post Mindbeam sets generative AI models to task on drug design, hunting for better pain meds

AI Challenge Competition Info Webinar Anonymous (not verified) Thu, 07/09/2026 - 12:39   22 July 2026 Join the AI-BOOST Info Webinar on 22 July at 11:00 CEST to learn more about the AI-BOOST Open Innovation Competition and how to apply. Main link https://www.f6s.com/ai-challenge-competition-info-webinar Related topics Creating a digital society eHealth, Wellbeing and Ageing Artificial intelligence AI in health

Large language models (LLMs) have shown strong performance on isolated psychiatric tasks, including dialogue, diagnosis, and treatment planning, yet existing benchmarks rarely simulate complete psychiatric clinical encounters. We introduce $\textbf{MentalHospital}$, a virtual evaluation environment for LLM-based psychiatric clinical encounters. MentalHospital instantiates the Subjective Interviewing, Objective Examination, Diagnostic Assessment, and Treatment Planning (S.O.A.P.) workflow, using

Free apps from Google, Samsung and Apple can help you track your diet, exercise and well-being — and provide vital information during emergencies.

As more people turn to chatbots for support, new research is exploring a potential role for AI in spotting early signs of depression.

Nurses across the United States are increasingly using artificial intelligence in their day-to-day work, but over 80 percent of those who participated in a new survey said the tech isn't accurate enough to rely on without verification. Abo ... (report_number: 7500)

This notice acknowledges the Secretary of the Department of Health and Human Services' (the Secretary's) receipt and review of Battelle Memorial Institute's 2025 Annual Activities Report to Congress. The Battelle Memorial Institute is the consensus-based entity (CBE) under a contract with the Secretary, as mandated by section 1890(b)(5) of the Social Security Act (the Act). The Secretary has reviewed CBE's 2025 Annual Report and is publishing the report in the Federal Register together with the

Artificial intelligence (AI) models for cervical cytology screening have achieved pooled accuracy and sensitivity values exceeding 90% in recent meta-analyses, and several commercial systems are now in clinical use. However, whether these results generalize across laboratories, scanners, and clinical settings depends on pre-analytical factors—sample preparation, staining, digitization, and annotation—that are known to introduce substantial variability into the data that models consume. This scop

BackgroundIn recent years, advancements in our understanding of the pathophysiological mechanisms underlying coronary artery disease (CAD) have introduced new challenges regarding the clinical application of traditional risk scores. While studies suggest that machine learning (ML) algorithms surpass traditional statistical methods in risk prediction, their conclusions are often derived from heterogeneous datasets and varying model structures, which restrict their generalizability and persuasive

Large language models (LLMs) exhibit remarkable capabilities but remain highly vulnerable to adversarial prompts and jailbreak attacks. Existing approaches primarily analyze these failures through input-output behaviors or attribution methods, offering limited insight into how adversarial perturbations alter the model's internal reasoning. Consequently, the mechanisms underlying unsafe or incorrect behaviors remain poorly understood. We introduce a mechanistic framework for diagnosing LLM vulner

Alight (NYSE: ALIT), a leading benefits administration provider of health, wealth and leave solutions, today announced a collaboration with BNY (NYSE: BNY), a global financial services platforms company, to launch a retirement solution designed to offer defined contribution (DC) and defined benefit (DB) plan sponsors and participants deeper support for plan administration and investing.

In long-horizon tasks, decision-relevant state is often scattered across an expanding trajectory, while the action agent must surface it and act. As trajectories grow, task requirements, environment facts, prior attempts, diagnoses, and open subgoals can be buried in the context window or pushed beyond it, failing to influence decisions when needed. We call this failure mode "behavioral state decay". We study memory as an active intervention mechanism rather than passive retrieval. A separate me

Current computational approaches for drug design typically focus on generating molecules conditioned on specific targets or general molecular properties, often neglecting the influence of disease context on target behavior and therapeutic outcomes. To address this gap, we introduce DrugGen-2, a novel generative model that designs small molecules conditioned on both disease ontology and target protein sequences. DrugGen-2 was developed by fine-tuning a pre-trained GPT-2 model on a curated dataset

The post DIVERSSITY wins the Innovation Factory Women Entrepreneurs 2026 with AI-driven mental health support for neurodiverse adolescents appeared first on AI for Good .

Automated segmentation of cervical-spine MRI is increasingly used in clinical workflows, yet no fairness audit exists for this anatomy. We show that auditing these segmentation tasks is complicated by a common property of modern segmentation datasets: expert-annotated gold labels are expensive, so abundant machine-generated (silver) labels are added to limit annotation cost. This matters because the reference used to judge a model can itself be biased. In this study, we present the first fairnes

Navigating intellectual property (IP) issues for new innovations has never been simple. With healthcare solutions based on artificial intelligence (AI), it can be especially complex. Innovators, ...

Become a changemaker in health systems globally with a cutting-edge Master's degree where policy, leadership, business management, and an innovation mindset converge. This MSc brings together ...

A startup co-developed by UCL alumni has taken part in the sought-after Y Combinator accelerator in San Francisco to develop its AI personal health assistant for people living with chronic illness.

Large language models (LLMs) have become significant providers of mental health support, yet they remain products of an attention economy whose operational and commercial targets favour sustained engagement over the friction that effective psychological support often requires. Developers' safety responses have been largely reactive, addressing the most visible and acute harms while subtler, longer-term patterns of risk (e.g., dependency, boundary erosion, the amplification of distorted beliefs)

Large language models (LLMs) have emerged as important tools in healthcare, showing growing potential for clinical reasoning and patient care. This survey examines recent progress in medical LLMs, focusing on reasoning applications and requirements. We present a dual-view approach that connects clinical practice with computational methods. On the clinical side, we establish a five-level competency scheme following Miller's Pyramid, progressing from knowledge recall to dynamic case management. On

Science works at a much slower pace than social media, opening a large window for early findings to be taken at face value and misinformation to spread.

Vision foundation models (VFMs) are increasingly being developed for radiological imaging, yet their definition, development and evaluation remain heterogeneous. We conducted a PRISMAScR scoping review of peer-reviewed studies published between January 2017 and March 2026 describing foundation models trained exclusively on radiological imaging data. Sixty-seven studies were included and mapped across three pillars: data scale and heterogeneity, architectural and pretraining scalability, and down

“AI will reshape medicine. The physicians who answer for the outcome must lead the way it enters patient care," write Afnan R. Tariq and Ami Bhatt.

On Techpoint Digest, we discuss how Starlink has frozen new sign-ups in seven Kenyan counties, how Andrea Aid wants to improve medical crowdfunding, and how South Africans claim Facebook is restricting accounts without warning.

IntroductionFetal health monitoring is critical for early identification of pregnancy-related risks. Manual interpretation of cardiotocography (CTG) signals is subjective and variable among healthcare professionals.MethodsA machine learning-based framework was developed to classify fetal health into Normal, Suspect, and Pathological categories using CTG-derived clinical features. The dataset was preprocessed through duplicate removal, normalization, class balancing using SMOTEENN, multicollinear

Medicine is inherently multimodal, requiring clinicians to synthesize information across diverse data streams. Yet the development of multimodal foundation models is constrained by limited access to large-scale, high-quality clinical data. Although PubMed Central (PMC) offers a complementary source of expert-authored image-text data, existing PMC-derived resources remain limited in fidelity, reproducibility, and clinical validation. We introduce MedPMC, an automated, continuously updatable frame

The optimization of long-horizon agents increasingly relies on reflection-based mechanisms, where a large language model (LLM) acts as an optimizer to diagnose agent failures and improve agent policies. However, real execution traces are difficult to use directly for optimization: large trace collections are often redundant and heterogeneous, making optimization inefficient and prone to overfitting to low-value failures; meanwhile, each individual trajectory also contains many irrelevant steps,

AI-Enabled Citiverse: Use Cases for Cities in the Age of AI – Public Safety, Health and Disaster Resilience 2026 ...

Large language models (LLMs) achieve promising results on medical question answering benchmarks, yet their use in public health is constrained by hallucinations and the rapid evolution of official guidance. Retrieval-Augmented Generation (RAG) mitigates these risks by grounding responses in an explicitly maintained corpus, but end-to-end performance depends critically on retrieval configuration and on evaluation beyond multiple-choice formats. We extend PubHealthBench, a question answering (QA)

Xbox CEO Asha Sharma says that turning Xbox around will take time.

Environmental DNA contained in a small sample of water, sand or even air can reveal the presence of people, wildlife and pathogens, helping researchers track where they’ve migrated.

Foundation Models for Electronic Health Records (FEMRs) are pretrained on large-scale structured patient data, enabling them to convert longitudinal patient trajectories into generalizable representations for diverse clinical prediction tasks. Despite their effectiveness, FEMRs remain black-box models, raising concerns about bias, interpretability, and clinical trust. To address this, we propose the first token-level explainability approach for FEMRs. We train a Transformer-based surrogate model

July 2026 - Since their adoption in 2015, the Sustainable Development Goals (SDGs) have delivered results at scale – bringing access to water, electricity and health care to billions. Without a ...

Imaging demand is growing faster than the radiology workforce can expand, and reporting backlogs cannot be resolved through training and recruitment alone. The most direct opportunity is reducing the time and effort radiologists spend producing reports, a task that requires interpreting images, integrating clinical history and prior studies, and drafting structured findings. We present Harrison.Rad 1.5 (HR1.5), a radiology-specific multimodal large language model that accepts interleaved text an

[The content of this article has been produced by our advertising partner.] The Radiology Department fields a steady flow of enquiries from many patients at the same time, arriving at all hours of the day and night, often stretching over days or months as patients consider their options or return after consulting their referring doctor. Each time a conversation resumes, staff have to pick up where it left off. The underlying work is complex too: 1,000+ distinct examination items, each with...

Andrea Aid, a Port Harcourt-based startup is building a medical crowdfunding platform that helps patients raise money for treatment by connecting them with donors.