A Survey on Precision Treatment for Humans Using Cognitive Machine Learning Techniques

Abstract

Personalized treatment (PT) is an emerging area in healthcare that provides personalized health. Personalized, targeted, or customized treatment gains more attention by providing the right treatment to the right person at the right time. Traditional treatment follows a whole systems approach, whereas PT unyokes the people into groups and helps them in rendering proper treatment based on disease risk. In PT, case by case analysis identifies the current status of each patient and performs detailed investigation of their health along with symptoms, signs, and difficulties. Case by case analysis also aids in constructing the clinical knowledge base according to the patient's needs. Thus, PT is a preventive medicine system enabling optimal therapy and cost-effective treatment. This chapter aims to explore how PT is served in works of literature by fusing machine learning (ML) and artificial intelligence (AI) techniques, which creates cognitive machine learning (CML). This chapter also explores the issues, challenges of traditional medicine, applications, models, pros, and cons of PT.