Clinical and Medical Engineering Live
ISSN: 2997-612X | DOI: 10.64030/2997-612X
Kennet Patrik, Fenella Chadwick
Early and accurate cancer detection significantly improves patient outcomes. This case study investigates the application of artificial intelligence (AI), specifically deep learning techniques for image analysis, in enhancing the early diagnosis of [breast cancer, lung cancer]. We explore the development and evaluation of an AI-powered system trained on a large dataset of medical images (mammograms, CT scans) to identify subtle anomalies indicative of malignancy. The system's performance is assessed in terms of sensitivity, specificity, and accuracy against traditional diagnostic methods. Preliminary results demonstrate the potential of AI to achieve comparable or even superior diagnostic accuracy, enabling earlier intervention and potentially improving patient survival rates. Challenges related to data privacy, algorithm interpretability, and clinical integration are also discussed.