Artificial Intelligence in Healthcare: A Reading Guide
Artificial intelligence is changing clinical work, health management and academic publishing at the same time. This guide collects the AI articles on The Health Topics, from critical appraisals of medical AI claims to large language models in clinical and scholarly work, machine learning, digital twins, fairness and governance.
Start here
- The Forbidden Forest of AI in Healthcare: Red Lines, Trojan Horses, and Yet-Uncharted Paths
- Medical AI’s 97 Percent Lie: The story of the driving school “champion”
- The Silent Paradox of the Digital Twin in Healthcare: Can “Better Care” and a “More Efficient System” Meet in the Same Model?
- Principles for Understanding Trust in Artificial Intelligence: A Conceptual Map and the Research Questions Left Open
- Navigating LLMs in Healthcare: Pitfalls and Potentials
Large language models and generative AI
- When “AI-Detected” Does Not Mean “AI-Written”: A Reading of a New Turnitin Study
- When AI Speaks Down to Patients
- Can Generative AI Strengthen Critical Thinking? A Pedagogical Framework for LLM Integration in Higher Education
- Analysis theories on artificial intelligence, ChatGPT, data science, and metaverse
- AI’s Role in Enhancing Literature Reviews
- Impact of Cognitive Bias on LLM Reasoning in Healthcare
- AI in Patient Education: Assessing Turkish Language Models
- Exploring the Human-AI Bond: Functional and Parasocial Value in ChatGPT Adoption
- The Layered Model as Intellectual Mining: Treating AI-Assisted Drafts as Valuable Ore
- Mapping AI Adoption in Major Diseases: A Bibliometric Study
- AI and Medical Writing: What Are the Points of Contention?
- AI Is Writing Medicine. Are We Okay With That?
- Who Is the Author Now? How AI Is Rewriting Academic Trust, Power, and Responsibility in 2025
- ChatGPT in Nursing: Applications, Advantages, and Challenges
- From Scarcity to Abundance: Scholars and Scholarship in AI’s Age
- Bridging the GenAI Divide: From Pilots to Profits
- Generative Agents: Modelling Social-Environmental Impacts on Mental Health
- Trust and Evidence in Medical AI
- AI Versus Human Judgment in Child Credibility Assessment
- Large Language Models in Healthcare: A Bibliometric Analysis
- GenAI’s Impact on Green Innovation for SMEs
- Rethinking Regulation for Artificial Intelligence
- AI Accuracy in Cardiovascular Pharmacology Education
- ChatGPT: Transforming Health, Education, and Economy
- ChatGPT: Italian Perceptions of Opportunities and Challenges
- ChatGPT versus Clinical Decision Support for Drug Interactions
- ChatGPT in Medicine: Benefits, Limits, and Risks
- ChatGPT for Healthcare Data Analysis: Validation and Framework
- ChatGPT in Healthcare Education: A Double-Edged Sword
- ChatGPT for Healthcare Needs from Patient Reviews
- Thematic Analysis with AI: A Step-by-Step Guide
- Sequential Diagnosis with Language Models
- AI-Assisted Systematic Literature Reviews: A GPT-4 System
- Generative AI for Health Technology Assessment: An ISPOR Report
- Generative AI’s Healthcare Transformation
- AI, Machine Learning, and Deep Learning in Oncology
- AI Clinical Decision Support for Hand Surgery
Machine learning and prediction
- Machine Learning in Surgical PROMs: A Critical Academic Appraisal and a Forward Research Agenda
- Predicting Creativity Among Nurses with Machine Learning: An Ambitious Contribution with Important Lessons for Future Research
- Beyond the Algorithm: Human Factors in Explainable AI and the Future of Clinical Trust
- Predicting and Explaining Medical Students’ Psychological Resilience: A Dual Perspective of Machine Learning and Path Analysis
- Artificial Intelligence in Predictive Healthcare: A Systematic Review
- Predicting Nurse Creativity with Machine Learning
- Nursing Entrepreneurial Ability: Influencing Factors and Development Strategies
- AI in Mental Health: A Bibliometric Analysis
- AI and Machine Learning in Health and Medicine: A 25-Year Analysis
- AI in Oncology: Global Research Trends and Challenges
- AI Against AMR: A Bibliometric Review
- Digital Determinants of Health: Data Poverty and AI/ML Bias
- Predicting Child Mortality in India Through Machine Learning
- Explainable AI for Mental Disorder Diagnosis in Children
- AI’s Role in Modern Drug Regulation
- Fair Machine Learning in Real-World Healthcare Data
- Machine Learning for Public Health Policy Evaluation
- Enhancing Health Policy Reviews with Machine Learning
- Predicting Healthcare Demand with Andersen’s Model and ML
- How to Choose the Right Variables in Health Services Machine Learning
Digital twins
AI in academic writing and peer review
- Research Integrity · Editorial AI · The Other Side of Disclosure
- A Reader’s Guide to the New Logic of AI in Scholarly Publishing
- Artificial Intelligence in Peer Review: A Seven-Level Framework
- Fabricated Citations in Medical Research: A Reader-Friendly Summary and Critical Review
- Algorithms Capture Style, Not Text: 10 Proofs of Producing the Human Trace in Academic Writing
More articles in this area
- Navigating AI Ethics: Principles, Lived Realities, and Power Structures
- AI and Medical Liability: A New Methodology
- AI Tools in Clinical Documentation: Reducing Burden and Time
- AI Strategies for Hospital Fall Prevention
- Transforming Electronic Health Records into Predictive Tools
- Artificial Intelligence Is Reshaping Health Systems—What the WHO Europe Readiness Report Really Says
- Artificial Intelligence and Scientific Writing: The Theseus Paradox
- AI Risk Management: A Bibliometric Analysis
- AI in Critical Illness: A Bibliometric Analysis
- AI in Chronic Disease Management: A Bibliometric Study
- AI’s Role in Non-Communicable Disease Detection
- AI Ethics in Business: A Thematic Evolution
- Digital Health, AI, and Evidence-Based Medicine in Future Physicians
- AI in Healthcare: Promises, Pitfalls, and Pathways Forward
- Neural Mechanisms of Hospital Decision-Making
- AI’s Role in Sustainable Hospital Management
- AI’s Impact on Healthcare: Efficiency, Accuracy, and Innovation
- AI in Healthcare Administration: Revolution or Risky Disruption?
- Physician Attitudes on AI in Primary Care
- AI in Medicine: A Bibliometric Analysis (2019-2023)
- AI Clinical Support and Healthcare Worker Satisfaction
- Quantum Computing’s Impact on Medical Sciences
- Process Mining in Healthcare: Characteristics and Challenges
- Artificial Intelligence in Medicine: Applications and Impact
- Global Regulation of AI Medical Devices
- AI in Online Learning: Supporting Shared Regulation
- Global AI Governance: Policy Frameworks in China, EU, and US
- Regulating AI: A Flawed Approach
- Governing AI: Beyond Risk-Based Regulation
- AI in Nursing Simulation and Education
- Blockchain Healthcare Systems: Security, Chaincode, and EHR Performance
- Fog Computing for Healthcare 4.0: Opportunities and Challenges
- Industry 4.0 and Health: Revolutionizing Healthcare
- AI Radiologist: Clinical Quality Report Generation with Large Models
- Unlocking Patient Resistance to AI in Healthcare
- Swiss Cheese Model for AI Safety
- AI’s Role in Systematic Reviews: The Elicit Example
- AI in Health Professions Education Assessment
- Addressing AI Fairness in Healthcare: A Comprehensive Review
- Evaluating AI in Healthcare: Crucial Protocols for Safety
- Impact of AI on Clinical Outcomes in Dentistry
- AI in Healthcare: Enhancing Patient Safety Through Risk Management
- Early Effectiveness of AI Insulin Delivery: Study Findings Explained
- Why AI Fails to Transform Hospital Practices
This guide is updated as new articles are published. Last updated: November 2026.