Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 15,161 to 15,170 of 212,780 articles

A Methodology for Creating Patient Relevant Questions Suitable for Evaluating AI Generated Health Advice.

Studies in health technology and informatics May 21, 2026
Artificial intelligence (AI) holds potential to assist with patient-facing communication. However, patients' interpretation and trust in AI-generated clinical responses remains underexplored. In this work, we describe a protocol for developing and va... read more 

Aligning AI-Native 6G Healthcare Systems with EU Ethical and Legal Frameworks.

Studies in health technology and informatics May 21, 2026
The convergence of AI, robotics, and 6G networks is reshaping healthcare through real-time This paper applies a structured regulatory-technical analysis to examine how the EU AI Act, GDPR, NIS2 Directive, and Medical Device Regulation apply within AI... read more 

Linking Explainability, Trust, and Use: A Framework for Clinical Decision Support.

Studies in health technology and informatics May 21, 2026
Adoption of AI-based clinical decision support systems (AI-CDSS) remains limited, largely due to insufficient trust in AI models, especially in high-risk healthcare scenarios. To address this, this research presents an initial conceptual model linkin... read more 

Developing a RAG-Based Chatbot for Healthcare: A Case Study of the HeartWise AI Chatbot.

Studies in health technology and informatics May 21, 2026
HeartWise is a proof-of-concept Retrieval Augmented Generation (RAG) chatbot supporting self-care in coronary artery disease. Eight simulated scenarios were used to assess preliminary performance. Six cases (75%) produced guideline-consistent respons... read more 

Real-World Application of a Machine Learning Pipeline for Overall Survival in Chronic Lymphocytic Leukemia.

Studies in health technology and informatics May 21, 2026
We developed a machine learning model and validated it using a large-scale, real-world cohort to predict overall survival in patients with Chronic Lymphocytic Leukemia (CLL). The model captured key survival trends between treatment eras. Individual-l... read more 

Physicians' Perspectives on Predictive Uncertainty in Machine Learning Models.

Studies in health technology and informatics May 21, 2026
We examined clinicians' perspectives on predictive uncertainty displayed alongside risk predictions using semi-structured interviews in a postoperative delirium dashboard prototype. While clinicians recognized the value of uncertainty information, th... read more 

Design and Early Evaluation of an Algorithmovigilance System.

Studies in health technology and informatics May 21, 2026
Algorithmovigilance, the proactive and ongoing monitoring of AI systems, is essential for safe and effective AI use in healthcare. We describe the early deployment experiences and assessment of an AI monitoring and operations system and provide desig... read more 

Designing for Trust: Exploring User Perceptions of AI Transparency in Healthcare.

Studies in health technology and informatics May 21, 2026
Transparency is frequently cited as a key ethical requirement for artificial intelligence (AI), yet its meaning remains ambiguous and often defined through a top-down technical or regulatory perspectives. The XpliCAI project adopts a user-centered pa... read more 

Beyond the Algorithm: Citizens Professionals Dialogue on the Use of Generative AI in Healthcare.

Studies in health technology and informatics May 21, 2026
Generative artificial intelligence (GAI) offers new opportunities to improve healthcare efficiency and quality, yet its adoption raises ethical and societal questions. Questions about transparency, equitability, accountability, data privacy, and the ... read more 

Governance of Artificial Intelligence in an Academic Health System After 2 Years.

Studies in health technology and informatics May 21, 2026
Artificial Intelligence requires a new approach to governance to manage the complexity of the algorithms themselves, implementation, and monitoring. At Oregon Health & Science University, an AI governance approach that used key AI frameworks to creat... read more 
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