Harvard AI in Clinical Medicine 2026

Original price was: $1,500.97.Current price is: $179.97.

Harvard AI in Clinical Medicine 2026. Recorded course for on-demand study, with downloadable digital materials and Google Drive access.

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Description

HARVARD • CLINICAL AI • 2026

AI in Clinical Medicine 2026

A comprehensive recorded program exploring how artificial intelligence is moving into real clinical practice — from machine learning and large language models to clinical decision support, ambient documentation, precision medicine, ethics, bias, regulation, and practical implementation.

RECORDED COURSE CLINICAL AI INSTANT ACCESS LIFETIME ACCESS ENGLISH
2026 Clinical AI Update
ML
Machine LearningCore concepts for clinicians
LLM
Large Language ModelsGenerative AI and clinical workflows
CDS
Decision SupportEHR tools, diagnosis and prediction
PM
Precision MedicineOncology, drug discovery and trials
ETH
Ethics & BiasFairness, privacy and responsible AI
IMP
ImplementationDeploying AI safely in practice
3 DaysProgram Scope
Clinical AICore Focus
RecordedOn-Demand
∞Lifetime Access
About the Course

Cut through the AI hype and understand what matters in clinical practice.

The program is built for clinicians who want a practical understanding of artificial intelligence without needing a technical background.

AI in Clinical Medicine 2026 begins with foundational concepts such as machine learning, deep learning, large language models, and the medical data infrastructure that supports clinical AI.

It then moves into real-world use cases including chatbots, ambient scribes, clinical decision-support systems, patient monitoring, disease prediction, medical education, drug development, precision oncology, and AI-powered clinical trial design.

The program also addresses responsible implementation, algorithmic bias, patient privacy, regulation, leadership, workflow integration, and the practical limitations clinicians need to understand before adopting AI tools.

Why explore this program

Understand machine learning, deep learning and LLMs
Review ambient scribes and generative AI workflows
Explore precision medicine and AI-enabled research
Understand ethics, bias, privacy and regulation
Learn practical clinical implementation frameworks
Study at your own pace with recorded access
Clinical Coverage

From AI foundations to real-world deployment.

The course connects technical concepts with the clinical, operational, ethical, and leadership questions that determine whether AI is actually useful in care.

AI

AI Foundations

Machine learning, deep learning, large language models, technical background for clinicians, and medical data as the backbone of AI systems.

CL

Clinical Applications

Clinical decision support, ambient documentation, chatbots, patient monitoring, diagnosis, outcome prediction, EHR integration, and specialty-specific use cases.

IN

Innovation & Precision Medicine

AI-designed therapeutics, drug development, clinical-trial design, precision oncology, personalized treatment, and AI-assisted research tools.

ER

Ethics, Regulation & Leadership

Ethics, algorithmic bias, fairness, privacy, law, regulation, responsible implementation, health-system leadership, and adoption strategy.

Course Leadership & Faculty

Meet the leaders behind the program.

Roles below follow the official Harvard 2026 faculty section: Maha Farhat and Samir Kendale are Course Directors; Isaac Kohane is featured as course faculty and delivers the opening keynote.

Maha Farhat, MD, MSc
Course Director

Maha Farhat, MD, MSc

Massachusetts General Hospital Division of Pulmonary and Critical Care Medicine

Gilbert S. Omenn Associate Professor of Biomedical Informatics

Associate Director, Bioinformatics and Integrative Genomics (BIG) PhD Track

Samir Kendale, MD, FASA
Course Director

Samir Kendale, MD, FASA

Assistant Professor of Anaesthesia, Harvard Medical School

Medical Director of Anesthesia Informatics, Beth Israel Lahey Health

Isaac Kohane, MD, PhD
Featured Faculty

Isaac Kohane, MD, PhD

Chair, Department of Biomedical Informatics, Harvard Medical School

Marion V. Nelson Professor of Biomedical Informatics, Harvard Medical School

Associate Professor of Medicine, Brigham and Women's Hospital

3-Day Curriculum

A practical progression from foundations to implementation.

The 2026 agenda moves from understanding AI, to ethics and advanced applications, to operational deployment across clinical specialties and healthcare organizations.

Day 1

Foundations, Generative AI & Precision Medicine

  • How AI is changing clinical care
  • Machine learning, deep learning and LLMs
  • Technical background for clinicians
  • Medical data as the backbone of AI
  • Chatbots and generative AI
  • AI in medical education
  • Ambient scribes
  • AI-designed therapeutics
  • Precision oncology
  • AI-powered clinical trials
Day 2

Ethics, Regulation, Bias & Advanced Clinical Use Cases

  • Ethics and AI in healthcare
  • Leadership in the digital era
  • AI law and regulation
  • Heart-failure telemetry and mHealth
  • Brain-computer interfaces
  • Chatbots in mental health
  • Bias in risk stratification
  • Robust, fair and private AI
  • Algorithmic bias in clinical scores
Day 3

Implementation, Workflow & Specialty Applications

  • Barriers to clinical AI implementation
  • Clinical decision support in the EHR
  • Implementing AI in smaller practices
  • Hidden risks of AI tools
  • AI and clinician burnout
  • Operational and financial considerations
  • Pathology, endocrinology and ophthalmology
  • Gastroenterology, critical care and radiology
  • Surgery and anesthesia applications
  • Ambient scribes, agentic AI and evidence search

Who should take this course?

Designed for clinicians and healthcare professionals who want to understand how AI can be evaluated and integrated into real patient-care environments.

Physicians Nurses Nurse Practitioners Physician Assistants Clinical Leaders Clinical Informaticians Healthcare Executives Researchers Allied Health Professionals Healthcare Professionals Interested in AI

Course Package

Recorded educational access designed for flexible self-paced review.

3 Days

Full Program Scope

Foundations, ethics, regulation, clinical applications, and implementation.

Recorded

On-Demand Sessions

Review the available educational presentations according to your own schedule.

Clinical AI

Practice-Focused Topics

Decision support, generative AI, ambient documentation, precision medicine, and more.

∞

Lifetime Access

Return to the available course materials whenever you need a refresher.

Frequently Asked Questions

Before you download.

Clear answers to common buyer questions.

Is this a live course?

No. This product contains recorded, on-demand educational materials for self-paced learning.

Does the course cover large language models?

Yes. Large language models are included within the foundational AI curriculum and broader generative-AI discussions.

Does it include practical clinical applications?

Yes. The program reviews clinical decision support, ambient scribes, patient monitoring, diagnosis and prediction, specialty-specific AI applications, and practical implementation strategies.

Are ethics, bias and regulation included?

Yes. Ethics, algorithmic bias, fairness, privacy, law, regulation, and responsible AI implementation are major areas of the program.

How will I receive access after purchase?

Access instructions are provided after your order is completed so you can begin reviewing the available course materials right away.

Does course access expire?

No. The recorded course package offered here includes lifetime access.

Does this recorded package include CME/CE credit or a certificate?

No. The recorded package offered here does not include CME/CE credit or an official certificate.

Important: This product provides recorded, on-demand educational materials and is not registration for the original live Harvard event. No CME/CE credit or official certificate is included with this recorded package.
RECORDED COURSE CLINICAL AI INSTANT ACCESS LIFETIME ACCESS
CLINICAL AI • DIGITAL MEDICINE • 2026

Understand what AI can actually do in clinical medicine.

Review machine learning, large language models, generative AI, clinical decision support, ambient documentation, precision medicine, ethics, regulation, specialty applications, and real-world implementation — at your own pace.

DOWNLOAD COURSE NOW RECORDED COURSE • CLINICAL AI • INSTANT ACCESS • LIFETIME ACCESS

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