Big Data and Artificial Intelligence (AI) in the medical field are versatile tools applicable in various sectors such as commercial, academic, government, and public. They encompass diverse data types, including biological, biometric, and electronic health records. Biological data may involve information stored in biobanks, while biometric data can include personal wellness data gathered from devices. Electronic health data primarily consists of patient medical records, along with demographic information and medical imaging. This article aims to extensively explore the advantages, challenges, and implications of employing Big Data and AI in the medical domain, with a specific focus on improving diagnostics, clinical decision-making, and health care. Additionally, it considers essential ethical and regulatory issues related to the integration of these technologies. The paper particularly emphasizes the positive impact of combining Big Data with AI, resulting in enhanced precision of predictive models for disease outbreaks and patient health risks, ultimately improving strategies for preventive care.