A nurse using a digital tablet to support chronic disease management and personalized patient care for an older adult. The image depicts digital health monitoring, clinical decision support, and AI-assisted chronic illness management in a modern healthcare setting
16 July
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Source: Created with DALL-E, an AI system by OpenAI; Copyright: N/A (AI-generated image); License: Public Domain (CC0) A comprehensive review finds AI-powered nursing tools improve prediction of health risks and reduce unnecessary hospital use, while more research is needed on patients’ emotional well-being. (Toronto, July 16, 2026) Artificial intelligence (AI) is helping nurses better predict health problems before they become emergencies, according to a new review of existing research published in JMIR Nursing. The study found that AI-based nursing interventions can improve the care of people living with chronic illnesses by identifying patients at greater risk of complications, reducing unplanned hospital visits, and potentially loweringRead More →

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27 May
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Source: Freepik. Copyright: Freepik License: CCBY A new viewpoint article published in JMIR Mental Health argues that AI systems should evaluate the reliability of human training and feedback data to improve safety in mental health applications. (Toronto, May 27, 2026) A new viewpoint article published in JMIR MentalHealth warns that artificial intelligence (AI) systems used in mental health settings may inherit and reinforce unreliable human input unless new safeguards are adopted. The paper, titled “When AI Colludes: ClinicalReliability of Training and Preference Data as a Trustworthy-AI Criterion,” calls for the “clinical reliability” of training data to become a core standard for trustworthy AI. The articleRead More →

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11 March
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Source: Freepik Copyright: Freepik License: CCBY AI Model Predicts Survival Outcomes for Bladder Cancer Patients with Newfound Accuracy (Toronto, March 11, 2026) Researchers at Fondazione Policlinico Universitario Agostino Gemelli IRCCS have developed a promising machine learning algorithm capable of predicting survival and cause of death for patients with bladder cancer undergoing radical cystectomy. The study, published in JMIR Perioperative Medicine, highlights a significant shift toward using artificial intelligence (AI) to personalize post-surgical care and improve prognostic accuracy. Radical cystectomy is a critical intervention for bladder cancer, yet roughly 50% of patients develop metastases within two years of the procedure. Traditional statistical models often struggle toRead More →

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17 November
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(Toronto, November 17, 2025) A new study published in the peer-reviewed journal JMIR Mental Health by JMIR Publications highlights a critical risk in the growing use of Large Language Models (LLMs) like GPT-4o by researchers: the frequent fabrication and inaccuracy of bibliographic citations. The findings underscore an urgent need for rigorous human verification and institutional safeguards to protect research integrity, particularly in specialized and less publicly known fields within mental health. Nearly 1 in 5 Citations Fabricated by GPT-4o in Literature Reviews The article, titled “Influence of Topic Familiarity and Prompt Specificity on Citation Fabrication in Mental Health Research Using Large Language Models: Experimental Study,”Read More →

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03 March
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Source: ChatGPTCopyright: N/A (AI generated image)License: Public Domain (CC0) A new machine learning study reveals that Wi-Fi motion sensors can detect depression in community-dwelling older adults, offering a nonintrusive alternative to wearable devices. (March 3, 2025) A new study published in JMIR Aging developed and tested an innovative artificial intelligence (AI) model called HOPE that uses Wi-Fi–based motion sensor data to detect depression in older adults. This study offers a nonintrusive alternative to wearable devices, improving accessibility and compliance among aging populations. The research, titled “Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study,” was published byRead More →

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29 March
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In a recent interview posted on JMIR TV, JMIR Publications’ CEO Dr Gunther Eysenbach speaks with Dr Andrew Taylor from Yale University School of Medicine about their paper titled “How Does ChatGPT Perform on the United States Medical Licensing Examination? The Implications of Large Language Models for Medical Education and Knowledge Assessment,” published in JMIR Medical Education.  The study examined how ChatGPT performed on the United States Medical Licensing Examination (USMLE) compared to other AI language models such as InstructGPT and GPT-3. The researchers found that ChatGPT’s performance on the exam was comparable to that of a third-year medical student in terms of medical knowledgeRead More →

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21 March
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Australian researchers have established a set of protocols for a research project in JMIR Research Protocols  that aims to explore whether humans will continue in meaningful decision-making roles in an AI-driven future. The researchers, Dr Nandini Doreswamy and Dr Louise Horstmanshof from Southern Cross University, found that there is a dearth of guidance in establishing whole sets of protocols for methods used in complex health research. They have now established protocols that focus on non-clinical health services such as health regulation and health policy. These health services can be complex, the researchers say, and even more extensive in their scope and scale than clinical healthcare.Read More →

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16 March
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A new paper published in the Journal of Medical Internet Research describes how generative models such as DALL-E 2, a novel deep learning model for text-to-image generation, could represent a promising future tool for image generation, augmentation, and manipulation in health care. Do generative models have sufficient medical domain knowledge to provide accurate and useful results? Dr Lisa C Adams and colleagues explore this topic in their latest viewpoint titled “What Does DALL-E 2 Know About Radiology?”  First introduced by OpenAI in April 2022, DALL-E 2 is an artificial intelligence (AI) tool that has gained popularity for generating novel photorealistic images or artwork based onRead More →

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03 March
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A study published on February 8, 2023, in JMIR Medical Education, a leading open access journal on digital medical education, evaluated the potential of ChatGPT, a natural language processing model, as a medical education tool. The study found that ChatGPT reaches the equivalent of a passing score for a third-year medical student. Conducted by researchers from Yale University School of Medicine’s Section for Biomedical Informatics and Data Science and University College Dublin, the study aimed to test the performance of ChatGPT and previous-generation large language models on the medical question-answering problem as part of the United States Medical Licensing Examination (USMLE) Step 1 and StepRead More →

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07 December
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JMIR Publications published “A Revised Hippocratic Oath for the Era of Digital Health” in the Journal of Medical Internet Research, which argues that the Hippocratic Oath, which contains a set of ethical rules designed to guide physicians through their profession, should be updated to reflect the new realities of digital health and articulate updated principles that govern the practice of modern medicine. The original Hippocratic Oath still embodies ideals that are timely and relevant even in the 21st century: To treat patients to the best of one’s ability To preserve a patient’s privacy To faithfully teach the art of medicine to the next generation DespiteRead More →