ABSTRACT
This chapter focuses on federated learning and its various applications, with an emphasis on how it can benefit the healthcare industry. Competing pharmaceutical businesses use federated learning to aggregate insights from many datasets into a machine learning model without revealing their raw data, how they distribute it across partners in the competition, or how they gain access to other servers. These are illustrations of how linking people and organizations may revolutionize medical research through federated learning in healthcare and collaborative machine learning. Federated learning makes it possible for researchers to work together more effectively in the pharmaceutical sector and to find novel medications. In Machine Learning and Deep Learning, to get revelations from medical data resultant from pathology, genetics radiology, cancer, etc., they have leapfrogged artificial intelligence innovation in the healthcare sector.
