Application of Machine Learning in Healthcare: An Analysis

Health care field is facing a lot of challenges due to the huge volume of people need medical support. The pandemic situation has created a lot of challenges to the healthcare field. This paper analyses how advancement in machine learning can be best utilized in improving health care services. Machine learning techniques are based on the idea of how systems can learn from the already existing data and can work with minimal human supervision. Thus machine learning has huge scope in healthcare. Machine learning algorithms can be effectively utilized for disease prediction, disease detection, providing personalized healthcare etc. These models can effectively predict the presence of diseases and also helps in detecting the diseases at earlier stage itself. Both supervised and unsupervised algorithms will be helpful in this field. Personalized healthcare applications aim to provide patient oriented healthcare services. Machine learning in combination with internet of things technologies made the personalized health care possible. The data collected from wearable devices and sensors can be effectively processed using machine learning algorithms and effective predictions can leads to quality of life improvements. In this chapter authors studies some of the existing applications of machine learning in healthcare field. Authors also propose a model that will add value to the existing applications.