+ HEALTH Background Discharge letters are essential for continuity of care, yet patients often misunderstand their con…± HEALTH Hematoxylin and Eosin (H&E) glass slide preparation is fundamental to histopathology. Pathologists' expertise…+ CLIMATE Traditional soil heavy metal risk assessments suffer from fragmented indices and poor logical integration. Co…± HEALTH Background Neonatal pneumothorax can progress rapidly, yet detection on supine chest radiographs remains chal…+ HEALTH T cell exhaustion has widespread implications for the progression and treatment of chronic diseases including…+ HEALTH Background Standard pulmonary arterial hypertension (PAH) risk models may not fully apply to PAH associated w…+ HEALTH Objectives To map and synthesize the scientific evidence regarding the use of Augmented Reality (AR) and Mixe…± HEALTH Objective To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovas…
TruaceTracing the truth around AIMonday, September 14, 2026
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Evidence-backed problem

Who Is in the Room? Stakeholder Perspectives on AI Recording in Pediatric Emergency Care

Artificial intelligence systems that record voice and video during pediatric emergencies are emerging as human-computer interaction (HCI) technologies with direct implications for clinical work, promising improvements in documentation, team performance, and post-event debriefing. Yet the perspectives of those most affected, including clinicians, parents, and child patients, remain largely absent from the design and governance of these technologies. This position paper argues that this has direct consequences for…

Proceedings of the 2026 ACM Interactive Health Conference · Health

Who Is in the Room? Stakeholder Perspectives on AI Recording in Pediatric Emergency Care
Young people’s perceptions and recommendations for conversational generative artificial intelligence in youth mental health
Evidence-backed gain

Young people’s perceptions and recommendations for conversational generative artificial intelligence in youth mental health

Conversational generative artificial intelligence agents (or genAI chatbots) could benefit youth mental health, yet young people's perspectives remain underexplored. We examined the Mental health Intelligence Agent (Mia), a genAI chatbot originally designed for professionals in Australian youth services. Following co-design, 32 young people participated in online workshops exploring their perceptions of genAI chatbots in youth mental health and to develop recommendations for reconceptualising Mia for consumers a…

Health
Ethical Concerns in Medical and Health-Related AI
Evidence-backed problem

Ethical Concerns in Medical and Health-Related AI

This perspective introduces the range of ethical concerns entailed by the widespread adoption of AI, particularly as they impact human health. It begins by (1) illustrating risks associated with all large-scale AI systems, then moves to (2) corporate and governmental applications of AI that affect human health. It overviews the ways (3) that patient usage of AI has affected human health; (4) that “passive” medical AI (like recording documents) and (5) “active” medical AI (like diagnosing and prescribing) may aff…

Health
Leveraging social media footprints for predicting college student anxiety: a machine learning approach
Evidence-backed gain

Leveraging social media footprints for predicting college student anxiety: a machine learning approach

Background Anxiety is one of the most prevalent mental health concerns among college students worldwide, yet traditional assessment methods relying on self-report questionnaires are time-consuming, susceptible to response bias, and difficult to scale. Social media platforms, which students use extensively, generate rich behavioral and linguistic data that may reflect underlying psychological states. This study investigates whether passively collected social media footprints are associated with anxiety scores amo…

Health
Exploring attitudes and acceptance of artificial intelligence in multiple sclerosis from the patient perspective
Evidence-backed gain

Exploring attitudes and acceptance of artificial intelligence in multiple sclerosis from the patient perspective

Artificial intelligence (AI) is increasingly being integrated into healthcare, particularly in data-intensive chronic diseases that rely on longitudinal monitoring and shared decision-making. Multiple sclerosis is a prototypical example of such care, but real-world benefit will depend on whether people accept AI support in different clinical roles. We conducted a cross-sectional, web-based survey among 241 people with MS (pwMS) to assess comfort with AI across eight clinical domains and to identify predictors of…

Health
Key challenges for delivering clinical impact with artificial intelligence
Evidence-backed problem

Key challenges for delivering clinical impact with artificial intelligence

BACKGROUND: Artificial intelligence (AI) research in healthcare is accelerating rapidly, with potential applications being demonstrated across various domains of medicine. However, there are currently limited examples of such techniques being successfully deployed into clinical practice. This article explores the main challenges and limitations of AI in healthcare, and considers the steps required to translate these potentially transformative technologies from research to clinical practice. MAIN BODY: Key challe…

Health
The Ethical and Legal Complexities of Regulating Companion AI Chatbots
Evidence-backed problem

The Ethical and Legal Complexities of Regulating Companion AI Chatbots

Companion AI chatbots are increasingly used to provide friendship, emotional support, and quasi-romantic relationships, with reported benefits for loneliness and mental health. At the same time, recent suicides and other serious harms allegedly linked to such systems expose gaps in existing ethical and legal frameworks. This article interrogates these gaps through four lenses: anthropomorphism,...

Health

Ossur H F Grjothals 5 Reykjavik Iceland recalls an AI-enabled medical device

The Rheo Knee bionic prosthetic is to be used exclusively for fittings of lower extremity amputations. RHEO KNEE uses Artificial Intelligence to continuously adapt to the users walking style and environment. The RHEO KNEE recognizes and responds immediately t… Recall reason: The firm is recalling Rheo Knee bionic prosthetic due to it being discovered during an internal audit of the service line that devices were released for distribution without fully going through the assembly process.

Health
Ossur H F Grjothals 5 Reykjavik Iceland recalls an AI-enabled medical device

Reveal linq: FDA malfunction report involving AI

The FDA received a malfunction report involving Reveal linq, made by Medtronic europe sarl. It was reported that the implantable cardiac monitor (icm) experienced false pause episodes due to undersensing. it was reported that representative stated the customer is concerned that the artificial intelligence (ai) algorithm adjudicated some pause episodes as false when they determined to be true. the icm remains in the patient. no patient complications have been reported as a result of this event.

Health
Reveal linq: FDA malfunction report involving AI

Accurhythm za420 (pause): FDA malfunction report involving AI

The FDA received a malfunction report involving Accurhythm za420 (pause), made by Medtronic, inc.. It was reported that true pause episodes were rejected as false by the artificial intelligence (ai) algorithm. no patient complications have been reported as a result of this event.

Health
Accurhythm za420 (pause): FDA malfunction report involving AI

Linq ii¿ insertable cardiac monitor: FDA malfunction report involving AI

The FDA received a malfunction report involving Linq ii¿ insertable cardiac monitor, made by Medtronic singapore operations. It was reported that true pause episodes were rejected as false by the artificial intelligence (ai) algorithm. it was further reported that the implantable cardiac monitor (icm) detected false ventricular tachycardia (vt) episodes. the icm remains in use. no patient complications have been reported as a result of this event.

Health
Linq ii¿ insertable cardiac monitor: FDA malfunction report involving AI

Clinical Impact of Artificial Intelligence-Based Triage Systems in Emergency Departments: A Systematic Review

Emergency departments (EDs) worldwide face increasing pressure to optimize triage processes amidst rising patient volumes and resource constraints. Artificial intelligence (AI) has emerged as a potential solution to enhance triage accuracy and efficiency, yet its real-world clinical impact remains inadequately characterized. We conducted a systematic review following Preferred Reporting Items f...

Health
Clinical Impact of Artificial Intelligence-Based Triage Systems in Emergency Departments: A Systematic Review

Real-World Impact and Educational Effectiveness of an AI-Powered Medical History-Taking System: Retrospective Propensity Score-Matched Cohort Study

Background Medical history-taking is a core clinical skill; yet, traditional teaching methods face challenges. We developed an artificial intelligence–powered medical history-taking training and evaluation system (AMTES) and established its technical feasibility as an extracurricular resource. Evidence on whether such tools improve learning outcomes when voluntarily embedded in routine curricul...

Health
Real-World Impact and Educational Effectiveness of an AI-Powered Medical History-Taking System: Retrospective Propensity Score-Matched Cohort Study