🔵 Advanced Stage: Cutting-Edge Models & Clinical Integration

🎯 Objective

To master advanced architectures, longitudinal and dynamic modeling, and clinical decision-making tools powered by AI.

🧠 Topics

Topic	Description
Transformers in Medical Imaging	Apply ViTs and Swin Transformers for imaging and clinical report understanding.
Reinforcement Learning in Healthcare	Use RL for optimizing treatment plans, surgery scheduling, and decision support.
LLMs for Medical Report Analysis	Leverage large language models (e.g., GPT, BioBERT) for summarizing and generating reports.
Generative AI (GANs, Diffusion)	Create synthetic medical data for augmentation or research simulation.
AI in Surgery & Robotics	Develop AI tools for navigation, robotic guidance, and intraoperative support.
Neural ODEs in Medical Imaging	Model disease progression or biological systems using continuous-time neural dynamics.
Longitudinal Disease Modeling	Track disease over time using sequential imaging or multi-visit EHR data.
AI in Drug Discovery & Personalized Medicine	Integrate imaging and molecular data to drive biomarker-guided therapies.