Advanced-Generative-AI-For-Skin-Diseases

Problem Statement Name: Advancing healthcare with multimodal generative AI.

Overview: Healthcare is poised for a revolution driven by Generative AI. Your challenge is to develop a multimodal AI-powered solution that significantly impacts the healthcare sector, from enhancing diagnostic processes to personalizing treatment plans and accelerating drug discovery. Leverage large language models, image generation, and other Gen AI technologies to create innovative solutions that improve patient outcomes, reduce costs, and advance the entire healthcare ecosystem.

Tech Stack:

• Python, PyTorch
• Hugging Face Transformers, Diffusers
• Multimodal Generative AI Models (e.g., GPT-4 with vision, PaLM 2, MedPaLM)
• Stable Diffusion or similar image generation models
• Healthcare APIs and DICOM standard for medical imaging
• Cloud Platforms (AWS HealthLake, Google Health Cloud, Azure Health Insights)

Restrictions:

• Use at least one large language model and one image generation model tailored to healthcare applications.
• Ensure adherence to healthcare industry standards and best practices

Exact Task:

• Mandatory Tasks:
  1. Develop a multimodal AI model that aids in diagnosing medical conditions using both text and medical imaging data.
  2. Create a generative AI system that can produce synthetic medical data for research and training purposes.
  3. Implement a feature that uses Gen AI to personalize treatment plans based on patient data and medical literature.
• Good-to-Have Tasks:
  1. Incorporate federated learning techniques to train your models while preserving patient data privacy.
  2. Develop a Gen AI-powered chatbot for patient engagement and preliminary symptom assessment.
  3. Implement metrics to evaluate the accuracy of AI-generated diagnoses, the quality of synthetic data, and the effectiveness of personalized treatment plans.
• Bonus Tasks:
  1. Use Gen AI to accelerate drug discovery by generating and evaluating potential molecular structures, with quantitative metrics on the novelty and potential efficacy of generated molecules.

Resources:

• Multimodal AI in Healthcare
• Generative AI for Drug Discovery
• Federated Learning in Medical AI