Breakthroughs in Artificial Intelligence in Breast Cancer Diagnosis and Prognosis: Radiomics and Pathology

As the most common cancer after lung cancer presently, breast cancer needs to gain extensive awareness of both general public and healthcare professionals. With continuous developments of technology researchers on medical science began to attach great significance to the integration of artificial intelligence (AI) and clinical diagnostics. With the purpose of enhancing early diagnosis and prognosis and implementing more effective and timely treatment for breast cancer, increased research efforts are currently aimed at applying AI to breast cancer detection and classification, opening up new avenues for improving patient care. The paper initially discusses the progress of AI in the diagnosis and prognosis of breast cancer and presents an overview of the existing literature of research in this area. It describes the main methods and procedures employed in AI-assisted diagnosis and response prediction with particular emphasis on radiological as well as pathological approaches. Comparative analysis is also provided comparing differences in sensitivity and specificity between clinicians and AI systems when interpreting images. Furthermore, the paper discusses existing challenges in the introduction of AI in clinical practice to assist clinicians’ diagnosis and carry out treatment. The major challenges include requirements for data volumes, standardization and ethical problems. Then, it predicted the future progress of AI technologies in diagnostics and prognosis of breast cancer, providing practical suggestions on promoting applications of AI in diagnosis, therapy and general use.