September 2026

the Madrid professor of surgery posted his own working laparoscopic appendectomy simulator, built with OpenAI's GPT-6 Astra: "just built a digital tool to simulate a lap appy", he wrote, framing it as bridging the gap…

The Vibe Code Doc is building withcline's clinical harness, a HIPAA-compliant system for routing models, adding practice context via PracticeBrain and designing custom EHRs

The MeDucation AI founder launched a free podcast station that pulls recent episodes by cancer type for oncologists and haematologists, alongside Oncopulse, a free AI agent that emails curated topic updates

former NHS GP Dr Keith Grimes's outfit released a free local viewer for the .ket XML reports GP practices receive from out-of-hours, NHS 111 and emergency systems, published explicitly as a proof of concept without…

The watchlisted Istanbul physician and Anthropic hackathon winner announced he is departing SignitApp to concentrate on his own healthcare and education products, Medkit included .

The watchlisted oncologist behind MeDucationAI released OncoPulse, a free AI agent for oncologists and haematologists that tracks FDA approvals, trial openings and treatment updates .

Oncologist and MeDucation AI founder Odabashian built a patient resource website without writing code or even a prompt, and released a free webinar series showing physicians exactly how he did it .

A UK GP who was quoted £75k to £100k to build a remote healthcare platform instead vibe-coded it himself in four days on Replit for roughly £165, shipping 16 features of "My Doctor"; Forbes cited it as a real…

GP partner Fahim Hussain MBChB MRCGP (Northern Health, West Yorkshire), who had never written a line of code, built the practice's private telemedicine platform on Replit in four days of evenings after his daughters…

physician and programmer Josh Mandel published a tool that exports all of your own health data from an Epic MyChart patient portal by replaying MyChart's own internal API calls from inside your authenticated browser…

by Rafaela Soares Rech, Carla Diniz Lopes Becker, Dieine Estela Bernieri Schiavon, Danielli Pires Vieira, Juliana Balbinot Hilgert, Fernando Neves Hugo Early and reliable screening for oropharyngeal dysphagia symptoms…

Background: Large language models (LLMs) are increasingly used as health information intermediaries. Whether they provide comparable accuracy and communication quality across languages has direct implications for…

Blind spots in AI-assisted healthcare evidence search: multiplatform evaluation of clinical retrieval gaps and risk-of-bias

EHRCON26 brought a public health doctor full circle, connecting openEHR, digital health, AI and a welcoming community focused on building better EHRs together.

Background: Internet search engines serve as primary gateways to cancer information; yet, the commercialization of health content within organic search results remains understudied. While covert promotional content;…

DentalGEN: a large-scale controllable generative AI framework for automated dental crown restoration

Development and validation of a machine learning model for the preoperative prediction of intractable hypoxemia in repeat lung surgery

Traditional research ethics governance was designed for bounded protocols, identifiable investigators, and temporally limited encounters with human participants. Data science health research (DSHR) disrupts that…

by Anita Burgun, Christina Khnaisser, Roxanne Dault, Jean-François Ethier Rare diseases affect millions worldwide and are associated with long diagnostic delays, limited access to treatments, and substantial challenges…

by Nianbo Xu, Andy Chun Hang Chen, Hanzhang Ruan, Donglin Yang, Renjie Liao, Xiaojuan Qi, Sze Wan Fong, Dandan Cao, Lu Yu, Yuanhua Huang, William Shu Biu Yeung, Ernest Hung Yu Ng, Yin Lau Lee Objective and reproducible…

Background: Hospitals continue to invest heavily to increase their level of digitalization. While advanced digital maturity is assumed to improve hospital performance, empirical evidence remains mixed. This tension is…

by Deepthi, Ashalatha Nayak, Rani Oomman Panicker Breast cancer is one of the leading causes of cancer-related mortality worldwide, and despite advances in clinical diagnosis, challenges such as inconclusive imaging…

Strabismus-Net mobile application for nine-gaze photograph-based strabismus diagnosis using dual-stream cross-attention and adaptive feature aggregation

by Ciara O’Sullivan, Tara Coppinger, Indika Dhanapala, Diarmuid Boyle, Alison Merrotsy People living with severe mental illness experience substantial health inequalities and high rates of premature mortality, largely…

Background: The traditional method for diagnosing obstructive sleep apnea (OSA) through polysomnography may be expensive and inaccessible. Recent developments in AI propose the use of photoplethysmography (PPG) to aid…

by Samar Thabet Jallad, Maysa Kassabry, Adel Taher Takruri Artificial intelligence (AI) and e-health literacy are increasingly relevant to nursing education; however, the relationship between nursing students’…

by Yuntao Wang, Mariluz De Ornelas, Matthew T. Studenski, Elizabeth Bossart, Siamak P. Nejad-Davarani, Yunze Yang We investigated the potential utility of large language models (LLMs) in supporting patient safety…

by Walid Al-Qerem, Anan Jarab, Judith Eberhardt, Khalda Smairan, Yousef Mimi, Maher Khdour Spirometric interpretation relies on reference equations, yet equations developed in one population or age range may not…

Background: Digital health technologies increasingly support long-term stroke management and rehabilitation, but technophobia may hinder their acceptance and sustained use among older patients with stroke. Evidence in…

Development and validation of a parsimonious AI-based mortality risk score for heart failure

Background: Large language models (LLMs) have the potential to improve the efficiency of evidence synthesis, but their reliability in performing complex tasks such as risk-of-bias (ROB) assessment in randomized…

Background: Pediatric health care requires distinct considerations, including caregiver involvement and developmental differences in cognition and communication as children gain autonomy, particularly as pediatric…

Implementation of remote patient monitoring for hypertension: a secondary analysis from electronic health record data

Large language model; assisted preoperative communication reduces patient anxiety and physician workload in prostate cancer: a prospective randomized phase II trial

Large language models as judges for clinical generative AI evaluation

LEME: open large language models for ophthalmology with advanced reasoning and clinical validation

Quantifying the plausibility gap in generative AI for surgical video generation with expert assessment

by Chao Zhu, Xin Zhang, Anneke van der Walt, Bruce Taylor, Mastura Monif, Tomas Kalincik, Jeanette Lechner-Scott, Katherine Buzzard, Trevor Kilpatrick, Michael Barnett, Zhen Zhou, Vilija Jokubaitis, Melissa Gresle,…

The application, development and challenge of digital twin in drug evaluation

Background: Digital health interventions (DHIs) offer scalable ways to reach youth. While DHI research often poses minimal risk, guardian permission is typically required for minors to participate. As a result,…

Background: Real-world gait assessment has gained momentum in populations with walking impairments, offering insights beyond standardized tests and supporting the integration of remote monitoring into clinical care.…

Background: Anticoagulants are high-alert medications with substantial risk of serious bleeding, yet dosing and prescribing errors remain common. Although clinical decision support systems (CDSSs) can mitigate these…

A multicenter assessment of human oversight of generative AI outputs in simulated clinical decision making

Background: Emergency triage of anterior circulation large vessel occlusion (LVO) is constrained by delays in vascular imaging, specialist interpretation, and transfer decision-making. Noncontrast computed tomography…

Background: Globally, health systems face increasing challenges due to improved life expectancy, rising levels of disease, greater expectations for health care, and growing expenditure. AI-based technologies are…

Background: Physician documentation requirements are a known contributor to clinician burnout, with the manual creation of brief hospital course (BHC) summaries being particularly time-consuming. Automating BHC…

Background: Failure to recognize clinical deterioration in hospitalized patients has prompted the development of rule-based electronic surveillance (RB-ES), predictive model; based electronic surveillance (PM-ES), and…

This article is a viewpoint: it presents the authors’ perspective, informed by a critical synthesis of the current literature at the intersection of generative AI (GenAI) technologies, public health communication, and…

Diabetes self-management in the digital health era: a concept analysis using natural language processing

Background: Digital overuse poses a significant threat to health through multiple pathways, including the deterioration of mental health and sleep disturbance. This issue has led to the development of digital…

by Ashiqur Rahman Khan, Nafisa Mahbub, Ridwan Al Aziz, Mahamudul Hassan Siddique, Zahidul Islam Sayeem Malaria remains a major public health challenge in sub-Saharan Africa, with Nigeria accounting for a substantial…

Enabling equitable global health AI with privacy‑enhancing technologies

by Jibril Bashir Adem, Anas Ali Alhur The rapid expansion of social media and the availability of Generative Artificial Intelligence (GenAI) technologies like ChatGPT and Gemini have significantly increased access to…

Background: Digital health technologies offer promising opportunities to support physical health. However, their acceptance, use, and associated benefits are not equally distributed across society. While existing…

by Weisheng Chen, Xinya Li, Zhongkai Qu, Ting Liu, Bo Chen, Liying Huang, Ningxia He, Zhigang Wang, Jun Lyu Pneumonia is a common infection in critically ill patients with poor outcomes, and its identification relies…

by Patrícia Pita Ferreira, Sara Soriano Longarón, Wiam Bouisaghouane, Jetse Goris, Anne H. Hoekman, Balázs Markos, Benjamin Maus, Giorgia Pozzi, Hadi Hasan, Indre Kalinauskaité, Jonáh Stunt, Joosje D. Kist, Judith van…

by Divya Sharma, Alice Rueda, Qiaowei Lin, Shakila Meshkat, Argyrios Perivolaris, Venkat Bhat Depression represents a complex, multifactorial disorder influenced by the interplay of biological, behavioral, and social…

Background: Social media use disorder (SMUD) has become an important concern in adolescent digital health. Although prior research has linked problematic social media use to psychological and family-related factors,…

AI adoption and workflow optimization following orchestration platform implementation and structured change management

Commission hosts Youth Policy Dialogue on the protection of minors online and cyberbullying

by Di Wu, Wenhao Cai, Chunmei Chen, Minting Chen, Yang Lv, Yilin Huang, Anthony Evans, Juan Lin, Diane Latawiec, Arjun Kattakayam, Rajarshi Mukherjee, Wei Huang, Qing Xia, Jie Xiao, Chunqiu Su, Jie Peng, Kuirong Jiang,…

Background: Vascular compromise remains the leading cause of free-flap failure. AI-based monitoring and prediction tools have emerged as a promising adjunct for postoperative free flap monitoring and early detection of…

DoseTailor for personalised tacrolimus dose optimisation across multicentre populations using interpretable AI

Background: The integration of digital health technology (DHT) into chronic kidney disease (CKD) care holds transformative potential for enhancing patient self-management and slowing disease progression. Despite the…

by Rocco Sheldon, Morya Wadodkar, Andrew Gan, Rachael Yip, Yimeng Zhang, Jyoti Baharani Outpatient clinic letters are a cornerstone of clinical communication but frequently exceed recommended reading levels, limiting…

Leveraging dynamic prompting for outcome prediction of cancer patients using large language models and electronic health record notes

Background: Medication nonadherence in patients with myocardial infarction (MI) is a key obstacle to managing cardiovascular disease. However, there is a lack of studies, particularly randomized controlled trials…

by Kalee Jack, Julie Tian, Viktoriia Kurkova, Setayesh Modanloo, Liz Dennett, Jasmine Noble, Andrew Greenshaw, Jake Hayward Workplace mental health issues are a prevalent concern. A potential solution is remote health…

Background: Unobtrusive digital monitoring technologies (UDMTs) enable continuous data collection beyond episodic clinical encounters and are increasingly incorporated into digital health clinical trials. However,…

Patient journey evaluation for consumer AI health assistants

Background: The COVID-19 pandemic transformed telemedicine in Poland from a niche service into a core mode of health care delivery, supported by nationwide eHealth infrastructure such as obligatory e-prescriptions and…

Preparing AI chatbots to respond to patient distress and suicidality in high-risk healthcare settings

Prospective multicenter evaluation of an autonomous robotic ultrasound system integrated with AI-assisted thyroid nodule assessment

Background: Large language models (LLMs) are increasingly being considered for clinical decision support, yet their safety in risk-based cervical screening management remains insufficiently characterized. Objective:…

Background: AI is increasingly being integrated into diabetes care, with growing evidence supporting its potential to improve clinical decision-making, risk prediction, and self-management. However, the lived…

Two Commission reports show impact of artificial intelligence and digital technologies on teaching and learning in Europe

by Joon Sang Baek, Sehwa Choi, Seojin Sung, Vasuki Rajaguru, Youngmok Park Tuberculosis (TB) remains a major global health challenge requiring prolonged treatment that is often complicated by adverse drug reactions…

AI Board holds its ninth meeting

DARE to wear: digital health promotion and disease prevention using wearable devices

External validation of AI assisted colposcopy using WHO dataset for cervical precancer and cancer detection

Outcome-grounded effect of clinically stigmatizing information on large language model emergency triage prioritization

by Kiran Bhattacharyya, Sreeram Kamabattula Deploying large language models (LLMs) in clinical settings is limited by security, reliability, latency, and accessibility concerns that favor smaller, on-device or…

by Mounzer Maaz, Samar Maaz, Islam Maaz, Randa Dardari, Helene Dardari, Dured Dardari Artificial intelligence can already automate selected diabetes tasks, but the evidence is uneven. Automated insulin delivery is…

by Diego Trujillo, Dulin Wang, Nathan Bahr, Tina Yi-Jin Hsieh, Byeongyeon Cho, Garth Meckler, Matthew Hansen, Carl Eriksson, Kyu Seo Kim, Steven Bedrick, Xiaoqian Jiang, Jeanne-Marie Guise Large language models (LLMs)…

the American College of Physicians reframes clinical AI as augmenting rather than substituting physician judgment and hangs liability on whoever acts on the output, the frame within which any clinician-built tool now…

Background: Machine learning (ML) and deep learning (DL) models have been developed for earlier recognition in hospitalized patients, but reported performance varies across datasets, prediction windows, care settings,…

by Zhipeng Yin, Zichong Wang, Min Chen, Ian Stockwell, Xin Ning, Jun Liu, Wenbin Zhang The application of question-answering (QA) systems in the medical domain has rapidly advanced, significantly improving patients’…

Benchmarking AI-generated thin-slice CT under clinical reconstruction conditions: a multicohort study

Clinical trials for digital health interventions: a rapid review of study independence and the developer effect

Commission welcomes the design of first Important Project of Common European Interest in AI

Conditional deep generative modeling of blood-based infrared spectra enables controlled in-silico phenotyping studies

Background: Digital health technologies are increasingly promoted as mechanisms to improve care coordination, enhance access, and reduce health care costs. However, whether community-level digitalization is associated…

Background: Virtual agents powered by dialogue trees have emerged as promising tools to overcome limitations of text-only psychological interventions in mental health treatment. Objective: This study evaluated whether…

by Nanziba Tasneem, Christian B. van der Pol, Ambreen Zahoor, Nitin Juggath, Kyle McGowan, Cynthia Lokker, Ashirbani Saha Radiology reports are often filled with medical jargon that limits patient understanding. Lay…

Background: The impact of biofeedback-based virtual reality (VR-BF) on pain and anxiety in pediatric surgical patients remains unexplored. Objective: The objective of this study was to evaluate the feasibility and…

Background: Large language models (LLMs) demonstrate strong performance on medical knowledge benchmarks, but their safe and effective use in clinical practice depends on posttraining adaptation rather than raw model…

Background: Recovery from opioid use disorder (OUD) is a complex, nonlinear process involving substantial health, psychological, and social challenges. Although online social support has been shown to benefit…

Background: Hepatopancreatobiliary (HPB) malignancies require complex treatment planning that often relies on multidisciplinary team (MDT) discussions. Large language models (LLMs) have recently been explored for…

by Rafi Al Attrach, Pedro Moreira, Rajna Fani, Renato Umeton, Amelia Fiske, Leo Anthony Celi Large-scale clinical databases offer opportunities for medical research, but their complexity creates barriers to effective…

Background: Individuals with opioid use disorder (OUD) who return to the community from incarceration face a high risk of fatal drug overdose. This mortality risk is related to significant barriers to accessing health…

Predicting calcification risk in prosthetic aortic valves: a hybrid physics-based and machine learning approach

Background: AI has the potential to support chest X-ray (CXR) triage in primary care, but adoption depends on whether clinicians perceive its outputs as credible, useful, and workable within routine clinical workflows.…

The evidence challenge facing large language models in medicine

The generative rearchitecture of antibody engineering shifts empirical discovery into intentional design

by Benjamin Rader, Dinesh K. Rai, Melissa L. Stewart, Sarah Lejfer, Sampath Chennuri, James Hartwell, Victor Moyano, Max H. Witwer, Peter C. Laussen, Heather L. Nelson, John S. Brownstein Despite growing interest in…

Digital technologies are increasingly integrated across health care systems; however, accumulating evidence shows that these tools often perform unevenly across population groups. Biases in AI-enabled tools can…

by Meixing Liao, Kai Huang, Eva Libeert, Bart Vanrumste, Simon Brumagne, Zhe Chen, Jean-Marie Aerts Prolonged sitting and standing are associated with health risks. Unlike generic sedentary behaviour monitoring based…

Background: AI-enabled digital health services are rapidly expanding within health care systems and are expected to improve health management and access to health information. However, rigorous empirical evidence on…

Background: Large language models (LLMs) are rapidly entering health care, but limited empirical data exist on health care professionals’ perceptions. Understanding health care professionals’ attitudes is essential for…

Auditing what was said: the epistemic promise and limits of ambient AI in clinical practice

Background: Generative AI video models are increasingly capable of producing complex depictions of mental health experiences, yet little is known about how these systems represent conditions such as depression. Because…

by Doohyun Park, Richul Oh, Jihyeon Baek, Kunho Bae The clinical value of artificial intelligence (AI) in fundus photography depends on workflow efficiency as well as diagnostic performance. We evaluated an AI-assisted…

Background: Hypertension is a leading preventable cause of cardiovascular disease, yet a substantial proportion of adults remain undiagnosed, limiting opportunities for early intervention. A predictive model was…

Publisher Correction: A scoping review on the mental health harms of LLM-based chatbots

Background: Quality of life (QoL) plays a crucial role in dementia care; however, QoL and its dynamic, context-dependent nature can be difficult to capture among people living with dementia due to challenges in memory…

Background: Social media has become an important channel for health information dissemination and public discussion of human papillomavirus (HPV) vaccination. Previous reviews have examined social media and HPV…

Background: Clinical notes offer rich, longitudinal insights into patient health trajectories. However, existing clinical sentiment analysis primarily evaluates overall note tone rather than the patient’s distinct…

Background: Digital health tools, such as health chatbots, may improve access to scalable health support, but adoption remains inconsistent. Existing models do not fully integrate technology acceptance factors with…

by Clark C. Freifeld, Kerlijn Van Assche, Alberto Olliaro, Martial Battain, Inthapavanh Kitignavong, Vayouly Vidhamaly, Phonepasith Boupha, Kem Boutsamay, Ngan Thi Do, Konnie Bellingham, Viengsavanh Pimxayvong,…

Background: Digital platforms are primary sources of sexual health information for young adults, yet they are widely perceived as unreliable. This tension between distrust and reliance remains undertheorized.…

Background: Health care service quality is inherently multidimensional; yet, the dominant practice in applied text analysis assigns each patient review to a single topic via Latent Dirichlet Allocation (LDA). This…

Background: AI is increasingly being integrated into health care workflows, with growing interest in AI systems for documentation, screening, triage, monitoring, and decision support. Mental health care is particularly…

Background: Large language models (LLMs) are increasingly being explored for clinical decision support, but their performance in audiology has not been systematically benchmarked using clinically grounded case…

by Oluwaseun Adebayo Bamodu, Sumaiya Nezam, Chen-Chih Chung Breast cancer remains the most commonly diagnosed malignancy among women globally, with disproportionately higher mortality rates in low- and middle-income…

Background: As generative AI (GenAI) becomes increasingly prevalent, its impact on physician mental health has garnered significant attention; yet, empirical evidence remains limited. Objective: This study aims to…

Background: Obstructive sleep apnea (OSA) is highly prevalent but remains substantially underdiagnosed. Polysomnography (PSG) is the reference standard, but its cost and limited availability constrain large-scale case…

Safety, efficacy and acceptability of human-GenAI single-session exposure-based intervention for academic anxiety: randomized controlled trials

by Sandra Van Mellaert, Martha S. Kreuzberg, Iris ten Klooster, Bert-Jan F. van Beijnum, Jan N. van Rijn, Monique Tabak eHealth interventions can support healthy lifestyle change for preventing and managing…

by Vlada Rozova, Liuliu Chen, Katrina Witt, Mike Conway, Jo Robinson, Karin Verspoor Adequate self-harm surveillance is a key part of suicide prevention. Our previous research demonstrated that an artificial…

A compliance walkthrough explains why prototyping platforms such as Lovable, Bubble and Replit have no BAA on standard tiers, so putting real patient data into an AI-built prototype is a breach before launch

by Jacqueline Toscano, King Yan Kwok, Meg Simione This pilot study aims to describe the process of developing a template that semi-automatically translates information from English to Spanish to improve caregivers’…

Medical Economics guidance notes that when a physician works directly with a developer to create an app for a specific patient population the need for HIPAA compliance is greater, pointing to HHS guidance as the…

Background: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder that affects the functioning and quality of life of individuals throughout their lifespan. Despite the extensive…

A domain-specific large language model for evidence-based nursing: development and multi-method evaluation of EviNurse

by Ahmad Agam, Emil Korsgaard, Troels Yding Haugstrup, Kasper Janus Grønn Emerek, Maria Weinkouff Pedersen, Massar Omar, Jacob Eifer Møller, Kristian Kragholm, Samuel Emil Schmidt, Peter Søgaard The study aimed to…

A global framework for artificial intelligence education in medicine: international working group recommendations

Background: Mobile health (mHealth) app effectiveness may be limited by low engagement. Increasing understanding of factors influencing engagement may help. Paid mHealth app subscription and renewal are two engagement…

The watchlisted surgeon analyses CDRH's new discussion paper proposing a competency-based regulatory path for generative AI medical devices (structured knowledge assessment, supervised practice with widening…

Background: To provide patients with gastric cancer with adequate health education information for effective overall management is crucial, while traditional manners exposed certain challenges. Conversational agents…

Background: Systems based on large language models (LLMs), multimodal LLMs, and vision-language foundation models are increasingly being evaluated for medical report generation in imaging and related clinical…

by Samah Khan, Georgeta Vaidean Patient education materials for cardiovascular disease (CVD) prevention frequently omit clinically important differences in disease manifestation, risk, and prevention between sexes.…

Background: Understanding how health-related rumor debunking evolves and spreads on social media is critical for public health communication and policy. Existing research, however, has been largely crisis-centered;…

Impact of LLM-supported patient education on patient perspectives and patient-reported outcomes: a mixed-methods systematic review

New recommendations based on extensive public engagement set out how the NHS could give patients faster access to AI advances with proportionate safeguards to protect patient safety and maintain high levels of trust.

by Karisa Parkington, Jithin T. Joseph, Katie Musleh, Marianne Rouleau-Tang, Annabelle Persaud, Alice Rueda, Bazen Gashaw Teferra, Huda F. Al-Shamali, Wanying Mao, Fatemeh Gholamali Nezhad, Lisa Burback, Yanbo Zhang,…

Background: Overdose and suicide due to nonprescribed fentanyl use have increased significantly, yet health care systems lack reliable methods to identify patients who use nonprescribed fentanyl. codes are inconsistent…

RDMA: cost effective agent-driven rare disease mining from electronic health records

Background: Postoperative outcome assessment is often based on discrete follow-up visits, limiting characterization of individual recovery trajectories, and the timely identification of adverse events (AEs).…

AI-derived carotid plaque vulnerability from B-mode ultrasound for cerebrovascular risk stratification: a multicenter cohort study

This commentary extends recent discussion of the solidarity gap associated with patient-facing AI by examining gaps in governance and risk allocation, health care professionals’ responsibilities in practice, and…

Background: New HIV cases among Malaysian men who have sex with men continue to rise, with young men who have sex with men (YMSM) accounting for 44% of new infections and experiencing high rates of comorbidities.…

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) induce clinically meaningful weight loss, but their real-world impact is constrained by poor medication persistence, treatment-limiting gastrointestinal adverse…

Impact of LLM assistance on physician decision-making: a multi-country randomized controlled trial

Background: Semantic interoperability in health care, essential for seamless integration of information systems, is partially achieved through the use of terminologies and common data standards that define the semantic…

Multimodal artificial intelligence integrating peritumoral MRI and clinical data stratifies meningioma recurrence risk after radiotherapy

Background: Large language model (LLM) agents capable of generating and executing statistical code from natural language may broaden access to clinical data analysis, yet which pipeline stages they perform reliably and…

by Shanyue Lin, Yudian Mao, Qian He, Wanyin Qi, Sanhong Zhang, Wei Li, Zhichao Zuo High-risk subtypes of invasive lung adenocarcinoma (IAC), particularly micropapillary- or solid-predominant patterns, are closely…

A paper in Clinical Chemistry and Laboratory Medicine by De Bruyne, Rommes, Fiers, Volders and Maes warns that AI-generated code for laboratory workflows appears functional but harbours subtle errors that make it…

Background: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation…

Background: Personalized dietary counseling is central to recurrence prevention in patients with urolithiasis, particularly after a 24-hour urine metabolic evaluation. However, translating quantitative metabolic…

Exploring generalizability and explainability of LLMs in classifying clinically rated suicidal ideation using heterogeneous data

Background: Digital health applications generate rich behavioral data; yet, how users transition between behavioral states remains poorly understood. Existing approaches show limited capacity to capture and represent…

Background: Differentiating among liver disease entities such as autoimmune liver disease (AILD), drug-induced liver injury (DILI), and chronic hepatitis B (CHB) remains clinically challenging due to overlapping…

Platforms for artificial intelligence-enabled infectious disease surveillance

Background: Federal and state school nutrition policies over the past 20 years have improved school meal nutritional quality, children’s diet quality, and childhood obesity prevalence in the United States. However,…

Background: In burn care, one of the most debated topics is the optimal treatment of patients with deep partial-thickness burns. With these patients, the decision must be made to perform early surgery or to wait and…

Unsupervised machine learning for placental disease using cell spatial organization

Background: Affirming care for lesbian, gay, bisexual, transgender, queer, and other individuals with diverse sexual orientations and gender identities (LGBTQ+) populations refers to culturally and clinically competent…

A five-phase evaluation framework for diagnostic and predictive medical artificial intelligence

Background: A substantial proportion of clinically relevant information remains locked in unstructured narrative documents, creating a bottleneck for clinical research, biobank annotation, registry development, and…

by Huey Yu Ng, Shamala Ramasamy, Saravanan Muthaiyah, Asnina Anandan, Seong Ting Chen, Thulasi Munohsamy, Gunasekar Thangarasu Digital health technologies (DHTs) such as patient portals, mobile applications, and…

AI models for medication adherence prediction: closing the gap to clinical readiness

by Jahliya Sisohor, Jatin P. Ambegaonkar, Bryndan Lindsey, Qi Wei, Yosef Shaul, Joel Martin Accurate assessment of body composition is essential for monitoring health status, fitness progress, and disease risk.…

Author Correction: Effect of a digital health behaviour change support system on cardiovascular disease risk in a randomized weight loss trial

by Pengby Ngor, Huy Rekol, Siv Sovannaroth, Po Ly, Eng Thyda, Sok Kimleng, Yoem Rattana, Ou Vunsokserey, Hem Vanna, Ran Sany, Chang Pumeoung, Steven Mellor, Rady Try, Pascal Ringwald, Richard J. Maude, Lisa J. White To…

Background: Generative AI (GenAI) tools powered by large language models (LLMs) are increasingly used by the public to seek health information. Unlike traditional web search, these systems generate conversational…

by Farnaz Kheiri, Shahryar Rahnamayan, Masoud Makrehchi Machine learning bias is a persistent challenge because it can create unfair outcomes, limit generalization, and reduce trust in real-world applications. A key…

Differences in tone of AI and care team responses to patient messages by patient demographics

Background: Digital health has provided caregivers with access to supportive resources without space-time restrictions. Caregivers’ digital health engagement behaviors can help them track their own health and that of…

Background: Pregnant women with affective or stress-related disorders face an elevated risk of perinatal depression and anxiety, yet evidence on digital nonpharmacologic interventions for this population remains…

by Mohan Wang, Caogen Hong, Zhengxing Huang, Fengmin Shao, Yue Gu We aimed to systematically analyze the historical evolution of artificial intelligence (AI) in end-stage renal disease (ESRD) management and propose a…

by Huan Li, Mark Iscoe, John Lutz, Carolina Diniz Hopper, Sabrina Fried, Josue Minaya, Caroline Raymond King, Olga Reykhart, Hyung Paek, Daniella Meeker, Edward R. Melnick, R. Andrew Taylor We developed and deploy a…

New partnership to create health innovation sandbox that will test promising new technologies and build evidence to accelerate the safe adoption of technologies, including AI, in the NHS.

Background: Large language models (LLMs) are increasingly demonstrating the potential to reach human-level performance in generating clinical summaries from patient-clinician conversations. LLMs are usually evaluated…

Prevailing ethical oversight of data science health research concentrates on privacy, consent, bias, and fairness. These concerns are necessary but insufficient, because each presupposes an answer to a prior question…

by Cleiane Gonçalves Oliveira, Marcos Flávio S. V. D’Angelo, Matheus P. Libório, Marcelo Perim Baldo, Hasheem Mannan Malaria remains a critical global health crisis, placing a disproportionate burden on children under…

Background: Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease influenced by genetic, epigenetic, ecological, and environmental factors, with a global prevalence of 7.7 to 13 per 100,000, and…

by Fardin Ganjkhanloo, Emmett Springer, Erik H. Hoyer, Daniel L. Young, Holley Farley, Kimia Ghobadi In this study, we aim to better align fall risk prediction from the Johns Hopkins Fall Risk Assessment Tool (JHFRAT)…

Background: General-purpose AI tools are increasingly accessible to mental health professionals, yet little is known about how these off-the-shelf systems are being integrated into routine therapeutic practice.…

Background: Generative AI (GAI) is rapidly transforming research practices, including qualitative methods in health research. While these tools offer efficiency in processing large volumes of textual data, concerns…

Generative deep learning reconstructs subcortical neural signals from cortical recordings for closed-loop brain stimulation

New ECCC call for proposals under the Digital Europe Programme is open for applications

the UK Pharmacists' Defence Association issued comprehensive guidance on 24 August establishing that pharmacists retain active oversight, professional judgement and accountability for AI-influenced decisions, covering…

Background: Problematic internet use (PIU) in adolescents often co-occurs with psychopathological symptoms. Social connectedness (SC) is a potential protective factor for both PIU and psychopathological symptoms, but…

by Jyoti Dalal, Douglas Teodoro, Minerva Rivas Velarde Despite the promising potential of Artificial Intelligence (AI) models to enhance health equities for persons with disabilities, poorly designed applications risk…

by Jesse Elder, Rahil Ryder, Mayuri Panditrao, Kaitlin Grosgebauer, Rebecca Katz, Lawrence Tello, Ellaison Carroll, Deva Borthwick, Chaman Kaur, Romario Smith, Victor Shiau, Will Wheeler, Emilia Reilly, Jennifer Myers,…

a 22 September poll found 34% of practices have built their own app or workflow tool in-house with AI and 8% tried and abandoned the build, and the accompanying guide covers a risk ladder, PHI exposure in coding tools,…

"Does this AI handoff have an owner?" (20 September) covers turning an AI-generated alert into a closed-loop task with acknowledgement, timing and escalation, and "Can 100 examples approve your AI?" (19 September)…

his piece makes the case for building badly on purpose, treating the attempt itself as education in what shipping clinical software actually involves .

A companion lab, published 20 September, on giving an AI-generated alert an accountable owner with acknowledgement, timing and escalation

A short interactive exercise from the clinicians.dev physician-builder community that asks the reader to find an unsupported claim in an AI-generated note, test a release rule, and see why zero observed errors is not…

The watchlist clinician-builder released a free video teaching physicians how to vibe code, arguing the gap between a clinic need and shipping is now about a weekend

A preprint review catalogues how vibe coding is being used across clinical, administrative and research domains, mapping the tools clinicians are building for themselves

A MSKCC-led team including Kollmeier (MD, radiation oncology) published a case study replacing an obsolete MATLAB radioactive-seed inventory system with a modern vibe-coded desktop application, a worked template for…

A Current Opinion in Ophthalmology paper by ophthalmologist-builders Fares Antaki and Pearse Keane gives eye clinicians a practical framework for building their own software through AI-assisted vibe coding workflows,…

A practical compliance checklist covering vendor BAA coverage, AI prompt hygiene, secrets management, access control, audit logging and third-party routing, written for non-developer builders including clinicians…

Bart Collet's 18 September edition covers an international group's assessment of AI teaching in medicine (fragmented, narrowly technical, disconnected from the ward) with a proposed fix across seven domains and 24…

A self-described busy surgical resident built Paper Saver, an iOS app with PubMed and Crossref search that stores research papers in one place, after noticing that papers sent by colleagues "rot in my email"; it is…

the curated clinical-technical network's fellows build and run a 48-hour hackathon (30 October to 1 November) on real clinical use cases, with tracks on clinical adoption and diagnostic AI on de-identified case data…

General Practice Registrars Australia announced a national working group and AI-confidence curriculum through which Australia's roughly 22,000 GP registrars can help co-design clinical AI tools, with twelve months of…

The UK's National Commission into the Regulation of AI in Healthcare (44 recommendations, published 10 September) proposes a readiness toolbox to help GP practices assess whether they have the governance, resources and…

Amplify Care's Healthcare Experience and Advancement Lab is running a free in-person workshop on 24 September 2026 in Kitchener, Ontario, teaching primary care clinicians to use vibe-coding tools to build workflow…

The Villages settled for $541.5M over AI-driven upcoding while Arintra raised $51M for autonomous medical coding the same week, highlighting the gap between vendor claims and provider attestation requirements that…

Mayo's AI office reports that keeping clinical models running costs more than building them, with drift monitoring, EHR upgrade revalidation and human ownership creating barriers for smaller systems, a…

The free, year-long NHS Clinical Entrepreneur Programme, which helps frontline clinical staff turn their ideas into products, opens Cohort 11 applications on 19 October 2026, with over 1,200 NHS staff having created…

OpenClinTech is accepting registrations for its September 2026 Clinician Engineer Bootcamp, an entry-level programme teaching clinically trained people to design and build full-stack applications, following a June 2026…