Healthcare

‘He who would do good to another must do it in Minute Particulars. General Good is the plea of the scoundrel, hypocrite and flatterer; For Art and Science cannot exist but in minutely organized Particulars’. 1 The poet William Blake expressed himself colourfully but also with good sense. What he writes of ‘Art and Science’ is true also of medical ethics. The papers included in this issue of the Journal of Medical Ethics illustrate this. They concern a range of issues whic

This paper examines the integration of artificial intelligence (AI) into cancer screening programmes, focusing on the associated equity challenges and resource allocation implications. While AI technologies promise significant benefits—such as improved diagnostic accuracy, shorter waiting times, reduced reliance on radiographers, and overall productivity gains and cost-effectiveness—current interventions disproportionately favour those already engaged in screening. This neglect of no

Prominent consequentialists who write about conscientious objection (CO) in healthcare, Julian Savulescu and Udo Schüklenk, both argue for the ‘incompatibility thesis’—the view that healthcare professionals ought never to be entitled to exercise a CO to absolve themselves of the responsibility to perform professional duties. I argue, contra Savulescu and Schüklenk, that consequentialists should advocate for a compromise position under which healthcare professionals are entitl

A number of authors have attempted to provide a consequentialist ethical justification for the accommodation of conscientious objectors. 1 Steve Clarke’s article is the most recent such effort. 2 Clarke essentially suggests that objectors should be accommodated because they would benefit from that accommodation, and that seems to make accommodation ethically desirable. He also acknowledges the empirical evidence demonstrating that accommodating objectors has detrimental health consequences

Clarke’s arguments in favour of permitting conscientious objection (CO) in healthcare and setting up registries are not new, but the consequentialist basis for them and the careful attention to seemingly deontological claims from prominent consequentialists about CO are novel. Though many of the arguments are persuasive, at least among those who already accept consequentialism of the form Clarke articulates, the analysis misses an important feature of CO (and a central point in debates abo

Clarke’s feature article 1 on conscientious objection (CO) in healthcare turns the spotlight on a medically relevant and theoretically ambitious topic. He well outlines background and prominent consequentialist positions towards CO and discusses registers as a promising approach to manage CO in practice that helps for dealing with the ‘incompatibility thesis’ beyond ‘conventional compromise’. 2 From our point of view, a register might be a beneficial way to enable h

Introduction The debate over conscientious objection (CO) in healthcare remains deeply polarised, often framed as a clash between professional obligations and individual moral integrity. In their consequentialist defence of permitting CO, Steve Clarke proposes a region-based register of non-objecting professionals as a mechanism to minimise reliance on referrals—what they aptly term a ‘fight without fighting’ approach. This commentary supports Clarke’s core argument but s

Introduction The permissibility of conscientious objection (CO) in healthcare presents a complex balance of benefits and harms, and philosophers disagree on whether it should be permitted at all. For example, consequentialists such as Udo Schuklenk argue that healthcare professionals should never be allowed to object, a position known as the ‘incompatibility thesis’. 1 Steve Clarke, however, believes that there is a positive consequentialist case for permitting CO in healthcare. 2 Th

In ‘A consequentialist case for permitting conscientious objection in healthcare,’ Steve Clarke proposes a publicly available registry for people seeking certain medical procedures (eg, abortion) to which some clinicians object for moral reasons. 1 The registry would list healthcare professionals (HCPs) available to perform those procedures, and patients could locate clinicians willing to help them and bypass the others. HCPs could also use the registry as an informational source for

Within a consequentialist framework, Steve Clarke opposes the complete exclusion of conscientious objection (CO) rights from medical professional duties. More specifically, he proposes a compromise to reduce the practical and moral costs of direct doctor–patient conflict: a system of region-based, regularly updated registers listing clinicians who do not object to specified CO-permissible procedures, together with a recommendation that patients (or referring clinicians) consult this inform

I feel privileged to receive so many thoughtful commentaries. Four commentaries focus on my proposal for a register system to manage conscientious objection (CO) in healthcare. Reasons of space meant I was unable to develop this proposal to any great extent in my article. 1 Hirschberg et al 2 explore practical and ethical issues involved in implementing a register system. I am pleased to have provoked further discussion of the proposal, and I thank them for their efforts. Boretti 3 offers three

The article examines China’s vaccination policy, focusing particularly on childhood immunisation and pandemic vaccines. Although China’s laws require individuals to engage in the vaccination decision-making process, the policy does not enforce mandatory vaccination through penalties. Instead, it emphasises informed decision-making, allowing and supporting individuals to choose whether to vaccinate or adopt other preventive measures based on their best health interests. The legal fram

‘Live tissue training’, using an anaesthetised live animal substituted for a human patient for the practice of surgical skills, is a controversial topic. Although simulator technologies have developed significantly for inclusion in many areas of surgical education, it is contested that training to manage traumatic injuries requires a model that can bleed and has a dynamic circulation. This article uses the published literature to explore the values at stake regarding live tissue trai

Recruitment challenges in clinical research are widespread, particularly for traditionally under-represented groups. Referral relationships—in which research partners and clinical partners agree to collaborate on selected research studies or programmes, with the expectation that the clinical partners refer appropriate patients as potential participants—may help alleviate these challenges. Referral relationships allow research partners access to expanded and more diverse pools of part

Breastfeeding provides critical insight into infant feeding competence and physiological health, yet objective monitoring remains difficult due to the intimate and internal nature of feeding. We present Mammal, a caregiver-worn computational garment that unobtrusively monitors breastfeeding without attaching sensors to the infant. Mammal leverages inter-body signal transmission through natural mouth-to-breast contact to capture infant cardiac and feeding-related acoustic signals on the caregiver

arXiv:2607.18446v1 Announce Type: cross Abstract: Purpose: Understanding how much of routine policing involves vulnerable people could inform resourcing, training, and multi-agency response, yet administrative data provide limited insight. We explore whether an LLM-based classification pipeline, developed on open-source US police data, can be adapted to estimate the prevalence of four vulnerability indicators - mental ill health, substance misuse, alcohol dependence, and homelessness - in UK pol

arXiv:2607.19075v1 Announce Type: cross Abstract: The rapid growth of the global aging population presents severe challenges to healthcare systems, necessitating efficient, equitable, and patient-centered care models. While Industrial Engineering and Operations Research (OR) provide robust optimization and decision-support tools to address these multidimensional complexities, current applications often remain fragmented. This paper presents a thematic review of 30 seminal studies at the intersec

Support-seeker' active engagement with received comments, e.g., showing positive sentiment and willingness to improve in the replies, can indicate the success of online health communities (OHCs). Their participation in other communities may correlate with their engagement in OHCs but remains under-explored. This paper analyzes 26, 725 seekers' behaviors in the other 40, 479 communities and their associations with seekers' engagement with received comments under their 78, 501 posts in 30 Baidu Ti

Mental health disorders (e.g., depression, anxiety, post-traumatic stress disorder (PTSD), bipolar disorder) represent a pressing global challenge, and early diagnosis with continuous monitoring is critical for effective intervention. However, traditional diagnostic methods, relying on patient self-reports and clinical interviews, are subjective and often miss subtle early warning signs, a problem compounded by stigma and limited access to care. In response, recent advances in artificial intelli

IntroductionNeural Architecture Search (NAS) effectively automates Deep Learning pipeline design but is prone to validation overfitting when applied to complex tasks, such as medical image analysis. To mitigate this and enhance generalization, researchers frequently integrate Deep Ensemble Learning (DEL) and data augmentation into the NAS workflow. However, the assumption that these methodologies do not negatively interfere in high-overfitting scenarios remains unproven.MethodsWe evaluated NAS,

This retrospective study enrolled 492 patients with scrub typhus in Jiangmen from 2013 to 2025. Clinical and laboratory data were analyzed using univariate logistic regression and LASSO regression to identify risk factors for severe illness. Seven machine-learning models, including logistic regression, support vector machine, random forest, XGBoost, Naive Bayes, k-nearest neighbor, and decision tree, were constructed and externally validated. Variable importance was ranked using SHAP analysis. M

The shape of a planar curve is the geometric information that remains once translation, rotation, scale and reparametrisation are removed and is of interest in many health applications, e.g. in neuroimaging. We propose a deep shape regression model for open planar curves that admits multimodal and high-dimensional covariates. Representing curves as complex-valued functions, we show that the conditional full Procrustes mean is the leading eigenfunction of the conditional covariance. To estimate t

Background: Effective communication is crucial for high-quality health care, but systemic barriers still disrupt patient-provider interactions. Research shows that communication failures are a major reason for preventable medical errors. These issues are linked to around 30% of malpractice claims and over 1744 deaths each year in the United States. In addition, hospitals lose about US $12 billion each year because of miscommunication. Despite the critical nature of this issue, the literature rem

Background: Digital health literacy is an essential skill for processing health-related information in today’s technology-driven society. Recent literature highlights deficits in digital health literacy among adolescents and legislative initiatives to secure its promotion have been introduced (eg, in the German Social Code Book V). However, few interventions target adolescents; existing programs often overlook critical aspects like graph literacy or lack applicability in schools and rigorous sci

As large language models and AI agents become the primary consumers of search results, document set quality determines the upper bound of downstream generation. Yet existing evaluation systems remain confined to scoring documents independently and aggregating via nDCG, ignoring inter-document interactions (redundancy, conflict, complementarity) and unable to answer what makes one document set better than another. To address these issues, we propose a complete evaluate-diagnose-optimize framework

Xaira Therapeutics is all in on data generation for model building! We talk with Bo Wang and Ci Chu about how and why.

Federated learning has emerged as a potential solution to privacy concerns associated with using sensitive health data for training predictive models, particularly in personalised cancer care. This research investigates whether federated learning can support the development of robust models for predicting tumour progression in breast cancer patients while addressing four critical deployment pillars: transparency, scalability, security, and fairness. This study evaluates a federated learning fram

Background: Lifestyle interventions for patients with prostate cancer have been shown to improve treatment adherence and quality of life. However, there remains a lack of large language models (LLMs) capable of delivering individualized and professional lifestyle recommendations under clearly defined medical safety boundaries and controlled evidence sources. Objective: This study aimed to develop and evaluate a supervised fine-tuned LLM—PCaPLMM_SFT (Prostate Cancer Patient Lifestyle Management M

As Texas schools face at least $600 million in federal funding cuts, multiple mental health programs, particularly those implemented in response to the pandemic and mass shootings, are at risk of losing funding. School programs focused on chronic absenteeism, mental wellness and crisis services that were created in response to the Uvalde school shooting, as […]

Anne Lord Bailey, who leads VA’s Strategic Initiatives Lab, said veterans who have used immersive tech have reported therapeutic benefits that extend beyond the conditions being treated by the headsets.

The Variational Quantum Eigensolver (VQE) is a leading algorithm for estimating molecular ground-state energies on near-term quantum hardware, with applications spanning quantum chemistry, materials science, and drug discovery. As VQE workloads are increasingly deployed through cloud-based ``VQE-as-a-service'' pipelines, they become exposed to adversaries such as compromised service components, malicious co-tenants, or insiders in the transpilation stack, any of which can corrupt results before

Whole-slide image (WSI) diagnosis requires identifying diagnostically relevant regions, examining them across magnifications, and integrating multi-scale evidence. However, most existing pathology benchmarks evaluate models on pre-cropped patches or pre-extracted slide features, leaving their ability to acquire evidence directly from gigapixel WSIs largely untested. We introduce PathAgentBench, a benchmark for evaluating evidence-seeking vision-language models (VLMs) across four complementary ca

States have made steady progress including students with disabilities in mainstream classrooms, an independent federal report finds, but lawmakers and advocates worry that headway will be lost as federal special education offices move from the Department of Education to Health and Human Services. Released this month, the Government Accountability Office report shows the number of […]

The mission has not succeeded in its core goals, and it’s using up military manpower and munitions at a time when the US is stretched on both, writes Daniel R. DePetris.

The report envisions a decade in which drones move goods, medical supplies, and information at a scale comparable to national infrastructure investments like highways and the electric grid. Potential applications include natural disaster detection drones that spot wildfire sources within minutes, medical supply chains that bypass ground congestion to reach rural hospitals, and nationwide fleets that continuously inspect bridges and power lines. Realizing this future, however, requires closing wh

Clinical NLP evaluation remains dominated by multiple-choice question answering (MCQA), which scores only final-answer accuracy and cannot detect when a model reaches the correct diagnosis while grounding it in irrelevant, absent, or contradictory evidence. We introduce MIRA-Ev, a clinical argument mining benchmark built on Spanish Médico Interno Residente (MIR) licensing-exam cases, re-annotated by expert clinicians with span-level premises, claims, and directed support/attack relations, and re

The Health Assistant chatbot is available "in beta for eligible US users," Samsung says.

Inferring contrast enhancement from one pre-contrast breast MRI slice is underdetermined: post-contrast appearance contains physiological information that is not uniquely encoded in baseline anatomy. Optimizing only paired pixel fidelity can suppress uncertain lesion enhancement, whereas adversarial or stochastic generative objectives can favor realistic post-contrast appearance without guaranteeing patient-specific lesion fidelity. We introduce MIRAGE, a residual 2D U-Net that combines global r

These three legal regimes are pulling in different directions, and the developers that navigate them well will be the ones that plan for all three from the start. The post The AI Tension In Healthcare: Patent Strategy, FDA Reality, And HIPAA Constraints appeared first on Above the Law .