AI in Healthcare Application
Applying machine learning to improve medical diagnostics
About This Project
This project involves developing a specialized AI model to diagnose medical conditions, with a particular focus on detecting pneumonia from X-ray images. The project addresses the unique challenges of working with medical data, including handling class imbalances, ensuring high precision and recall for critical diagnoses, and incorporating domain-specific medical knowledge. A key component of the project is the implementation of explainability techniques using tools like LIME to provide transparent insights into the model's decision-making process, which is crucial for building trust with healthcare professionals.
Core Concepts
- Medical image analysis
- Class imbalance handling techniques
- Model explainability for healthcare
- Domain-specific data preprocessing
- Performance evaluation for medical applications
- Healthcare regulatory compliance
Key Knowledge/Skills
- Medical data analysis
- Computer vision for healthcare
- Model explainability (LIME, SHAP)
- Healthcare-specific regulations
- Ethical considerations in medical AI
- Interpretability in neural networks
Coursework Covered
AI in Healthcare (or Bio Business & Industry)