Autonomous AI for Precision Medicine and Strategic ROI

Aim

Course Objectives

Syllabus

Module 1: The Diagnostic Engine & Vision Systems

• Transition from Classical CNNs to Vision Transformers (ViTs) for enhanced medical image analysis.
• Address the “Black Box” problem using Saliency Maps and Explainable AI (XAI) for clinical interpretability.
• Hands-on Lab: Tool: MONAI (Medical Open Network for AI)
• Exercise: Fine-tune pre-trained Med-ViT models for multi-class classification of medical imagery (Chest X-rays or Histopathology slides).
• Outcome: Visualize attention weights to validate clinical decision markers.

Module 2: Data Sovereignty & Synthetic Patient Modeling

• Explore the “Data Silo” paradox and balance HIPAA/GDPR compliance with AI training requirements.
• Utilize Generative AI to create Digital Twins simulating disease progression and clinical trials.
• Hands-on Lab: Tools: Gretel.ai / YData Fabric
• Exercise: Generate privacy-preserving synthetic EHR datasets from seed data.
• Outcome: Produce statistically accurate, shareable datasets bypassing IRB/Ethics Committee bottlenecks

Module 3: Clinical Deployment & Agentic Assistance

• Build Agentic AI agents for autonomous summarization and clinical pathway suggestions.
• Ensure interoperability by integrating AI outputs with legacy hospital workflows using HL7 FHIR standards.
• Hands-On Tools: LangChain, Streamlit, Cytoscape, NetworkX, CellDesigner
• Exercise: Develop a “Clinical Co-Pilot” dashboard that parses unstructured clinician notes, maps to ICD-11 codes, and visualizes molecular networks for actionable insights.
• Outcome: Deploy a functional web-based interface demonstrating real-world ROI and integrated clinical intelligence.

Who Should Enrol?

Course Outcomes

Meet Your Mentor(s)

DR. HARISHCHANDER ANANDARAM

Assistant Professor

Dr Harishchander Anandaram is an Assistant Professor at Centre for Excellence in Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India. He received his Ph.D. Degree in Bioengineering from Sathyabama Institute of Science and Technology, Chennai, in 2020. . . . In his PhD thesis, he worked on pharmacogenomics and miRNA- regulated networks in psoriasis, a joint project with Georgetown University, USA, JIPMER, INDIA, CIBA, INDIA, and ILS, INDIA. His thesis illustrated a multi-disciplinary approach by combining computational biophysics and molecular biology machine learning. Also, he had the opportunity to collaborate with international researchers and have publications in reputed international journals in bioinformatics and systems biology simultaneously. He has received the prestigious “Young Scientist Award” from “The Melinda Gates Foundation” for his research abstract on “The Implications of miRNA Dynamics in Infectious Diseases”. To date, he has reviewed more than 200 manuscripts in systems biology. He is currently working on predicting Novel lead molecules and biomarkers using computational techniques to target inflammatory pathways associated with infectious and autoimmune disorders.