Artificial Intelligence Medical Compendium

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

Showing 14,971 to 14,980 of 212,565 articles

Advances and Trends in Clinical Information Systems: From AI to Machine Learning Applications and Beyond.

Studies in health technology and informatics
Clinical Information systems (CIS) are a technological pillar of modern healthcare, enabling data driven decision-making, care coordination and patient centered care. This scoping review investigates how CIS are currently being studied globally, with... read more 

Exploring Healthcare Providers' Expectations and Perceptions of AI Machine Learning Decision Tree Models in Healthcare.

Studies in health technology and informatics
This paper investigates healthcare policymakers' and professionals' perceptions of Artificial Intelligence (AI) Machine Learning (ML) Decision Tree Models and their potential effects on clinical work processes. Semi-structured interviews with Dutch p... read more 

Exploring the Personalisation of Digital Cognitive Rehabilitation in Multiple Sclerosis Through Wearable Data and Machine Learning.

Studies in health technology and informatics
Cognitive impairment is a frequent, disabling symptom of multiple sclerosis (MS). Digital interventions may help people with MS maintain or improve cognition, but effectiveness varies between individuals. This exploratory study examines the feasibili... read more 

A Zoo of AI Transparency Indicators: What Do Users Want (and Need) in Hospitals?

Studies in health technology and informatics
Artificial intelligence (AI), whether generative, specialized, or agent-based, is increasingly integrated into the daily lives of many citizens. In healthcare, several applications are already in clinical use, influencing patient care. Yet, our under... read more 

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

Studies in health technology and informatics
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
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
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
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
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
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