Abstract:
The term “artificial intelligence” is generally used to describe computer-based systems that can perceive and derive data from their environment, and then use statistical algorithms to process that data in order to produce results intended to achieve pre-determined goals. The entire health care cycle, from pre-clinical to clinical, and from individualized to epidemic demands, requires a holistic approach. In recent years, deep learning and algorithmic problem-solving programmes have made it possible for machines to more closely mimic human analytical ability and decision-making than ever before. The power is shifting from narrow to broad Artificial Intelligence (AI) applications as they become more widely used. The pace and magnitude of the changes that artificial intelligence (hereinafter referred as AI) technologies are bringing about magnificent change posing problems for both society and every individual. Technological advancement is essential to guarantee that more advanced AI systems may be used in a way that respects human rights and ensures that the rewards of innovation are distributed fairly. The development of public health policies should be guided by this needs-based approach, which will also provide guidance for future. Collecting patient data and images to test AI algorithms becomes difficult due to the dispersion of medical data across numerous Electronic Health Records (EHR) and IT platforms. In this research paper the researcher will focus on the requirement a framework in which the abilities of humans and machines are combined to enhance one another.
