Predictive Analytics for Early Cancer Detection Using Machine Learning and Generative AI
Ritu Gautam, Prableen Kaur, Manik Sharma · 2025
Generative artificial intelligence (GAI) is rapidly transforming the landscape of cancer diagnosis, offering novel solutions to long-standing challenges. By leveraging complex algorithms and deep learning techniques, generative adversarial networks can analyze and interpret medical images with remarkable accuracy, often surpassing human capabilities. Crucially, generative AI can address limitations associated with traditional cancer diagnosis methods by generating synthetic medical images to augment limited datasets, improving the performance of diagnostic models; enhancing the resolution and quality of medical images, enabling more precise identification of malignant features; and enabling personalized medicine approaches by generating synthetic data that reflects individual patient characteristics. This chapter explores the burgeoning field of generative AI in cancer diagnosis, highlighting its potential to revolutionize early detection, improve diagnostic accuracy, and ultimately contribute to more effective treatment strategies. Also, a detailed comparison of other machine learning techniques with generative AI is analyzed. Finally, a novel design of promising smart diagnostic frameworks is proposed using machine learning and generative AI.