Lung Cancer Detection System
Business Problem – AI Powered Lung Imaging
India faces a high burden of lung diseases—TB, COPD, lung cancer, and silicosis—especially in rural and underserved regions with limited access to radiologists. The delay in diagnosis leads to poor patient outcomes. There’s a pressing need for AI-powered diagnostic tools that are both accurate and accessible in low-resource environments with intermittent internet.
Objectives
- Maximize early detection and diagnostic efficiency of lung diseases using AI-powered chest X-ray analysis across all healthcare settings.
Constraints
- Minimize infrastructure, connectivity, and expertise barriers to ensure seamless AI deployment in low-resource settings.
Success Criteria
1. Business Success Criteria
Maximize diagnostic reach and healthcare impact while minimizing delays and adoption barriers
2. ML Success Criteria
Maximize model accuracy and interpretability while minimizing diagnostic errors and bias.
3. Economic Success Criteria
Maximize cost-effectiveness and scalability while minimizing operational and deployment costs.