# AI for Clinicians

- Institution: IIT Madras
- Department: Multidisciplinary
- Taught by: Prof. Balaji Srinivasan, Prof. Ganapathy Krishnamurthi
- Level: Graduate
- Language: English
- Source: [NPTEL](https://nptel.ac.in/courses/127106006)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/127106006)
- Who can watch: Teens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Artificial intelligence is being adopted across clinical settings at a rapid pace creating a need for rigorous understanding of the foundations and applications of these methods for clinical practitioners and decision makers.

This course provides a systematic introduction to AI for clinicians, covering the intuitions underlying modern deep learning. It covers the principal model architectures encountered in healthcare, and the data considerations that determine what AI systems can and cannot do.

Topics progress from supervised learning and deep neural networks through generative models and agentic systems, with sustained attention to evaluation methodology, algorithmic bias, explainability, and regulatory frameworks.

The course is intended for clinical practitioners and decision makers seeking both the conceptual literacy to critically appraise AI in the literature and in practice, and the decision-making vocabulary required for institutional roles in AI adoption and governance.

Intended audience: MBBS students, postgraduate medical trainees, practicing clinicians, clinician-researchers, and healthcare administrators who want a rigorous but non-mathematical introduction to AI in clinical practice, evaluation, adoption, and governance.

Prerequisites: Should have clinical background. Ideally, at least a 2nd year medical student. Ideally must have done a biostatistics course

## Lectures

1. [What Is AI? An overview](https://invisiblenetwork.ai/learn/nptel/127106006/59f0bbb9a026) (YouTube)
2. [The AI Continuum I: Rules to Statistics](https://invisiblenetwork.ai/learn/nptel/127106006/f73dae60e990) (YouTube)
3. [The AI Continuum II: Machine Learning to Foundation Models](https://invisiblenetwork.ai/learn/nptel/127106006/656bfeac7fad) (YouTube)
4. [What Does the Model See? Encodings and representations](https://invisiblenetwork.ai/learn/nptel/127106006/c09488a950a1) (YouTube)
5. [Mathematical Functions and Learning from Data](https://invisiblenetwork.ai/learn/nptel/127106006/668c308bcb4e) (YouTube)
6. [Regression, Classification, and Types of Learning](https://invisiblenetwork.ai/learn/nptel/127106006/0575838b9361) (YouTube)
7. [Generalisation: Learning Beyond the Training Data](https://invisiblenetwork.ai/learn/nptel/127106006/164db234d178) (YouTube)
8. [Neural Networks as Flexible Learned Functtions](https://invisiblenetwork.ai/learn/nptel/127106006/f64ebbadc266) (YouTube)
9. [Learning Features and Representations](https://invisiblenetwork.ai/learn/nptel/127106006/1a3a3ed00b66) (YouTube)
10. [Convolutional Neural Networks for Medical Images](https://invisiblenetwork.ai/learn/nptel/127106006/c0c03fd5da0b) (YouTube)
11. [Medical Image Tasks: Classification, Detection, Segmentation and Regression](https://invisiblenetwork.ai/learn/nptel/127106006/869662cc6880) (YouTube)
12. [Modeling Sequences with RNNs](https://invisiblenetwork.ai/learn/nptel/127106006/5f7bedc96139) (YouTube)
13. [Tokens and Embeddings](https://invisiblenetwork.ai/learn/nptel/127106006/c780ed929d83) (YouTube)
14. [The Attention Mechanism: Deciding What Context Matters](https://invisiblenetwork.ai/learn/nptel/127106006/d54516aa8be7) (YouTube)
15. [The Transformer Architecture and Large Language Models](https://invisiblenetwork.ai/learn/nptel/127106006/1dd61ecb30b6) (YouTube)
16. [Basics of Medical image processing](https://invisiblenetwork.ai/learn/nptel/127106006/31e244edaa16) (YouTube)
17. [Basics of Clinical Text processing](https://invisiblenetwork.ai/learn/nptel/127106006/be5ece7db4f0) (YouTube)
18. [Clinical AI Evaluations I](https://invisiblenetwork.ai/learn/nptel/127106006/34ab30e3a8da) (YouTube)
19. [Clinical AI Evaluations II](https://invisiblenetwork.ai/learn/nptel/127106006/f0537109ae44) (YouTube)
20. [Generative models in Clinical workflow](https://invisiblenetwork.ai/learn/nptel/127106006/9fdb4f75169a) (YouTube)
21. [Medical Agent workflow](https://invisiblenetwork.ai/learn/nptel/127106006/7fe71cfe8a86) (YouTube)
22. [Clinical AI Agents](https://invisiblenetwork.ai/learn/nptel/127106006/55b66cefd159) (YouTube)
23. [Foundation Models - 1](https://invisiblenetwork.ai/learn/nptel/127106006/ff0bb06196c3) (YouTube)
24. [Foundation Models - 2](https://invisiblenetwork.ai/learn/nptel/127106006/e006f43eeb75) (YouTube)
25. [Foundation Models - 3](https://invisiblenetwork.ai/learn/nptel/127106006/a9d652cf7188) (YouTube)
26. [Foundation Models - 4](https://invisiblenetwork.ai/learn/nptel/127106006/5d684f387553) (YouTube)