AI Made Simple : An IRIA initiative
June 29, 2026 2026-10-14 12:14AI Made Simple : An IRIA initiative
3-Minute AI Clinics
One concept. Three minutes. Clear, practical, radiology-focused AI learning for every IRIA member.
Episode 02: What is Machine Learning?
Speaker: Dr. Amit Kharat
Discover what machine learning is, how computers learn from data, and why this technology is transforming the future of radiology.
Episode 03: How AI Learns from Medical Images
Speaker: Dr. Arjun Kalyanpur
Teleradiology Pioneer • AI Innovator
Understand how artificial intelligence learns from data and the fundamental principles that enable AI systems to recognize patterns and support clinical decision-making in radiology.
Episode 04: What is Ground Truth?
Speaker: Dr. Sarang Ingole
Radiologist • AI Educator
Discover why trustworthy AI begins with high-quality ground truth, and how radiologists play a vital role in creating the accurate data that powers AI.
Episode 05: Why Data Matters More Than Algorithms
Speaker: Dr. Anjali Agarwal
Radiologist • AI Educator
Explore why the quality, diversity, and relevance of data have a greater impact on AI performance than even the most advanced algorithms.
Episode 06: How Much Data Does AI Need?
Speaker: Dr. Praveen Shastry
Radiologist • AI Innovator
Learn why AI doesn’t simply need more data—it needs high-quality, diverse, and representative data to perform reliably in real-world clinical practice.
Episode 07: Can AI learn without labels?
Speaker: Dr. Devasenathipathy Kandasamy
Episode 08: Why AI Sometimes Gets It Wrong?
Speaker: Dr. Bagyam Raghavan
Senior Radiologist • Professor of Practice, IIT Madras
Understand why AI can make mistakes, the factors that influence its predictions, and why human oversight remains essential in clinical AI.
Episode 09 : Ultimate Radiology Mythbuster
Speaker: Dr. Suvrankar Datta
Simons Ashoka Early Career Fellow • Faculty Fellow, Koita Centre for Digital Health, Ashoka University
Challenge some of the common myths surrounding AI in radiology and discover what the evidence really tells us about its role in clinical practice.
Episode 10: Three Ways AI Reads Scans
Speaker: Dr. Annamalai
Radiologist • PhD Fellow, IIT Madras
Explore three fundamental ways AI can interpret medical images and understand how different approaches enable AI to detect, analyse, and characterize findings on scans.
Episode 11: Training, Validation and Testing Dataset
Speaker: Dr. Pradeeba Sridar
Assistant Professor, IIT Madras
Understand how datasets are divided for training, validating and testing AI models, and why each stage is essential for developing reliable AI.
Episode 12: Internal vs External Validation
Speaker: Dr. Pradosh Kumar Sarangi , AIIMS Deoghar
Understand the difference between internal and external validation, and why testing AI across new datasets and settings is essential to establish its real-world reliability.
Episode 13: What is Model Overfitting and Underfitting?
Speaker: Dr. Kritika Rangarajan
Associate Professor, AIIMS Delhi
Understand why AI models can either learn too much or too little from their training data—and how overfitting and underfitting affect model performance.
Episode 14: Effect of Data Shift on AI Performance in Radiology
Speaker: Dr. Rajul Rastogi
Episode 15: Foundation Models in Radiology
Speaker: Dr. Amit Gupta
AIIMS, New Delhi
Discover what foundation models are, how they are transforming AI in medical imaging, and their potential to support a wide range of applications in radiology.
