Interactive Virtual Consultation and Disease Diagnosis Using Machine Learning Approach

Abstract

Businesses that provide care remotely are far from the scope of virtual care. It offers a delivery channel for particular patient populations with applications that do not need in-person examinations or presence, even though it cannot be assumed to be the solution to all health-related questions. According to the scoping reviews, virtual care includes a significant information generation method called disease diagnosis, considered as the very first step towards treating the illness. Along with video conferencing technologies for consulting the doctors to achieve care supervision. Application of rehabilitation, remote consultation, and emergency services are efficient ways to use in attention to achieve well-being. Machine learning is one such way to achieve disease diagnosis based on information provided by the user with a high accuracy using various approaches. In this chapter, a novel approach of random forest approach with modifications is used.