AI Medical Compendium

Development of a Classifier for Metabolic Subtypes of Nasopharyngeal Carcinoma to Guide Personalized Immunotherapy Strategies: Biomarker Analysis of the Phase III CONTINUUM and DIPPER Trials.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology Mar 6, 2026

PURPOSE: Personalized immunotherapy strategies are urgently needed for patients with locoregionally advanced nasopharyngeal carcinoma (NPC). We aim to identify biomarkers predictive of immunotherapy benefits, using data from the phase III CONTINUUM (... read more

AI-Driven Mental Health Support for Caregivers of Individuals With Alzheimer Disease: Systematic Literature Review and Development of a Conceptual Framework.

JMIR mental health Mar 6, 2026

BACKGROUND: Caregivers supporting individuals with Alzheimer disease and related dementias (AD/ADRD) frequently encounter prolonged emotional strain, psychological distress, and social isolation, yet their needs are largely overlooked in current tech... read more

Exploring Feature Priorities and User Needs in Developing Virtual Study Assistants.

JMIR formative research Mar 6, 2026

This formative research explored health science researchers' perspectives on the development of an artificial intelligence-based virtual study assistant and identified 8 potential features and their priorities. read more

Comparison of Emotional Content in Text Responses From Physicians and AI Chatbots to Patient Health Queries: Cross-Sectional Study.

Journal of medical Internet research Mar 6, 2026

BACKGROUND: Surveys show that many people are willing to use generative artificial intelligence (AI) for health questions. Prior research has largely focused on chatbot accuracy, with some studies finding that both physicians and consumers overwhelmi... read more

Leveraging Naturalistic Driving Digital Biomarkers for Early Mild Cognitive Impairment Detection: Deep Learning Strategies.

JMIR medical informatics Mar 6, 2026

BACKGROUND: Alzheimer disease and related dementias are increasing worldwide, with early detection during the mild cognitive impairment (MCI) stage critical for timely intervention. Driving behavior, which reflects everyday cognitive functioning, has... read more

Trustworthy AI in Digital Health: A Comprehensive Review of Robustness and Explainability.

Progress in biomedical engineering (Bristol, England) Mar 6, 2026

Ensuring trust in AI systems is essential for the safe and ethical integration of machine learning (ML) systems into high-stakes domains such as digital health. Key dimensions, including robustness, explainability, fairness, accountability, and priva... read more

Strategies to Improve the Stability and Translation of Therapeutic mRNAs.

Annual review of chemical and biomolecular engineering Mar 6, 2026

Therapeutic messenger RNAs (mRNAs) offer a versatile platform for treating a wide range of diseases, but their clinical efficacy hinges on optimizing both stability and translational efficiency. This review summarizes recent advances in strategies to... read more

Improving Clinicians' Digital and Artificial Intelligence-Related Competence Within Healthcare Organizations in the United States: A Strategic Framework.

Applied clinical informatics Mar 6, 2026

INTRODUCTION: In recent years, there has been an emerging wave of artificial intelligence (AI) and digital tools in healthcare, thereby revolutionizing clinical practice. As health systems are increasingly utilizing these tools as a means to improve ... read more

Current State of Artificial Intelligence Adoption and Implementation in Neuroradiology Departments: Insights from a U.S. National Survey.

AJNR. American journal of neuroradiology Mar 6, 2026

BACKGROUND AND PURPOSE: Artificial intelligence (AI) is rapidly transforming medical imaging, yet its integration into neuroradiology remains uneven. This survey-based study assesses AI usage, tools, applications, barriers, and future expectations am... read more

Radiomics-based ultrasOund Model for differentiating Uterine Sarcomas from leiomyomas (ROMUS): a retrospective pilot Multicenter Italian Trials in Ovarian Cancer (MITO) study.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology Mar 6, 2026

OBJECTIVE: To develop machine-learning models that incorporate clinical information and radiomics features extracted from ultrasound images to distinguish uterine sarcomas from leiomyomas. METHODS: This retrospective, multicenter, pilot case-control ... read more

Artificial Intelligence Medical Compendium