Data Augmented Technology Assisted Medical Decision Making
Learn to use AI/ML for enhanced medical diagnoses. Explore ethical considerations and critically evaluate AI studies.
Course Cost
₹ 2,699
Beginner
Skill Level
10 Hours
Self-paced lessons
This course teaches healthcare professionals how to effectively use AI and machine learning to augment diagnostic decision-making. Designed for medical students, residents, fellows, physicians, advanced practice providers, and nurses, it covers the crucial role, strengths, and limitations of AI/ML in evidence-based medicine. Students learn to evaluate machine learning studies for bias, apply ML outputs to diagnostic decisions, and identify legal and ethical issues in healthcare AI. The curriculum includes foundational biostatistics, critical appraisal of AI/ML studies, and practical skills for using AI to enhance the diagnostic process.
What you'll learn
Describe the role, strengths, and limitations of AI/ML in evidence-based medical decision making
Evaluate machine learning studies for bias and systematic error
Apply machine learning study results and outputs to diagnostic decisions
Interpret statistical measures used to evaluate ML model performance
Critically appraise AI/ML studies and determine their clinical applicability
Identify legal and ethical issues in healthcare AI/ML use
Understand the sources and dimensions of algorithmic bias in healthcare
Apply best practices for AI/ML use in clinical settings
Skills you'll gain
This course includes:
3 Hours PreRecorded video
18 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 4 modules in this course
This course introduces healthcare professionals to the use of AI and machine learning in medical decision-making. It covers the fundamentals of AI/ML in healthcare, including data analysis, model development, and evaluation. Students learn to critically appraise AI/ML studies, understand statistical measures used in model evaluation, and apply ML outputs to clinical decisions. The curriculum also addresses ethical and legal considerations in healthcare AI, including bias, privacy, and governance. By the end of the course, participants will be equipped to effectively use AI/ML technologies to augment their diagnostic processes while navigating the associated challenges and ethical considerations.
Introduction to Artificial Intelligence and Machine Learning
Module 1 · 2 Hours to complete
Foundational Biostatistics and Epidemiology in AI/ML for Health Care Professionals
Module 2 · 3 Hours to complete
Using AI/ML to Augment Diagnostic Decisions
Module 3 · 2 Hours to complete
Ethical and Legal Use of AI/ML in the Diagnostic Process
Module 4 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.



