The collection of data during breast cancer screening holds significant potential for improving patient outcomes in the realm of data scienceData science (DS). As the field of data science continues to evolve, the integration of technology with medicine offers a promising avenue for the development of personalized or precision medicine. By utilizing a multiomic approach, which incorporates multiple datasets, outcomes can be achieved that surpass those of single data analyses. Data mining and machine learning techniques are already being employed in the medical field and are being tested for integration into precision medicine. However, it is crucial to understand the associated challenges and risks in the long term. Protecting the privacy of patients is of utmost importance, as the data collected is closely tied to individual patients. Therefore, it is essential to maintain ethical boundaries in clinical and intellectual pursuits. Furthermore, the successful integration of technology into precision medicine requires standardization and interdisciplinary collaboration across all fields. In this chapter, we will investigate the utilization of artificial intelligence (AI) in the field of oncology, focusing specifically on its role in cancer prognosis, prediction, and treatment selection. We will examine the ways in which AI and machine learning (ML) are employed to enhance healthcare outcomes and accuracy. Furthermore, the chapter will discuss the potential applications of AI and ML algorithms in cancer prediction, emphasizing their potential to revolutionize cancer research, diagnosis, and rehabilitation.Data science (DS)