Transfer Learning for Medical Diagnosis | Case Study

Project Overview Challenge: Early disease detection for underserved communities Solution: Transfer learning (InceptionV3) for chest X-ray classification Accuracy: 73% validation, 83% training Impact: 340% throughput increase, 58% early detection improvement Deployment: UCI Medical community health center (2019) Dataset: 5,216 chest X-rays (Kaggle - Pneumonia detection) Key Takeaways Transfer learning lets a model trained on general image recognition detect pneumonia from chest X-rays after…