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Getting Started on Artificial Intelligence in Health Care and Clinical Research: Includes Rigor Checklist for Authors
Chandan K Sen1, Deeptankar DeMazumder1,2
1McGowan Institute for Regenerative Medicine, Departments of Surgery & Cardiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Advances in Wound Care
|October 3, 2025
Summary
Artificial intelligence (AI) offers new biomedical discovery and healthcare paradigms. This roadmap guides researchers and clinicians in applying AI rigorously, focusing on human-AI collaboration for responsible innovation.
Area of Science:
- Biomedical research and healthcare
Background:
- Artificial intelligence (AI) is revolutionizing biomedical research and healthcare.
- The INTERNIST-1 system at the University of Pittsburgh in the 1970s pioneered AI in healthcare with diagnostic reasoning.
- Foundational concepts include data engineering, knowledge representation, and symbolic AI.
Purpose of the Study:
- To provide a comprehensive roadmap for understanding and applying AI in biomedical science and healthcare.
- To guide researchers, clinicians, and reviewers on rigorous and relevant AI implementation.
- To foster human-AI collaboration for transformative innovation.
Main Methods:
- Structured into three tiers: foundations, core techniques, and applications.
- Explores foundational concepts like data engineering and symbolic AI.
- Details core techniques (expert systems, machine learning, deep learning, explainable AI) and applications (NLP, computer vision, robotics).
Main Results:
- AI integration spans discovery, diagnosis, and decision-making in healthcare.
- Clinical examples demonstrate AI's role in wound care, image analysis, and predictive modeling.
- Addresses ethical considerations, bias mitigation, and workforce development for AI adoption.
Conclusions:
- Successful AI adoption in healthcare requires a focus on people and systematic workforce development.
- Emphasizes the importance of AI literacy among clinicians and researchers.
- Advocates for responsible innovation through human-AI collaboration, moving beyond hype.
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