AI in Medicine 2026

A Practical Guide to using AI in Diagnosis, Risk Assessment, Treatment, and Clinical Research

What you’ll learn
Discuss the role of AI in healthcare.
Apply AI tools to support clinical diagnosis.
Use AI risk prediction tools to triage and predict patient outcomes.
Use AI to assist with treatment selection and clinical reasoning.
Find out key recommendations in clinical guidelines and updates in local regulations using AI.
Incorporate AI into clinical research and quality improvement projects.

Requirements
No prerequisites.
This course includes guidance on how to use AI tools.

Description
Transform your clinical career with practical, real-world AI skills. No programming or coding.

AI in clinical medicine is no longer experimental. According to a Microsoft and IDC study, 79 percent of healthcare organizations are already using AI in some form, with an average return on investment realized within 14 months. Multi‑center deep learning models have demonstrated the ability to predict sepsis 3 to 4 hours before clinical onset. The global AI in healthcare market was valued at approximately USD 30 billion and is projected to exceed USD 500 billion by 2032 to 2033, growing at annual rates of over 38 percent.

Healthcare is evolving rapidly, and artificial intelligence (AI) is becoming one of the most important tools for clinicians.

This course is designed for physicians, residents, medical students, nurses, pharmacists, and other professionals and students who want a practical, accessible introduction to using AI safely and effectively in clinical practice. No technical background is required.

The course instructor is a US-trained professor of medicine with over two decades of clinical, teaching, and research experience. He was board certified in 2002, after completing residency training at the University of Rochester, New York.

Throughout the course, you will learn how AI is used in diagnosis, documentation, medical imaging, ECG interpretation, risk prediction, clinical decision-making, and even research and quality improvement. The goal is to help you build confidence, reduce workflow burdens, improve patient care, and stay competitive in a changing healthcare landscape.

Whether you feel curious, cautious, or excited about AI, this course gives practical applications you can begin using immediately.

What You Will Learn

• How AI tools assist in making a diagnosis, including documentation support and clinical learning

• How to use AI tools to assist with treatment planning, guideline retrieval, literature summaries, and clinical reasoning

• How AI can support research planning, sample size calculation, survey design, and manuscript writing

Who this course is for
Physicians and residents who want to use AI safely and effectively in diagnosis, treatment decisions, and clinical workflows.
Medical students, and students in nursing, pharmacy, physician assistant/associate, nurse practitioner, veterinary medicine, and other healthcare fields
Nurses and nurse practitioners interested in AI-supported documentation, risk scoring, patient monitoring, and workflow optimization.
Healthcare administrators, QI leaders, and clinical researchers exploring how AI can enhance operational efficiency, research design, and quality improvement.
Anyone working in healthcare who wants a practical, non-technical introduction to AI’s real-world applications, limitations, and future impact.