Telemedicine using Machine Learning: A Boon

Abstract

Telemedicine is a part of e-Health that employs information communication technologies (ICT) to transmit healthcare information required for educational and therapeutic purposes. Telehealth attempts to overcome the challenges in the delivery of health services due to distance, time, and challenging landscapes. It plays a significant role during floods and earthquakes. It enables better access and cost-effectiveness in both developing and developed world locations. The health sector has been dramatically influenced and affected by the Covid-19 pandemic with the adoption of improved technology that has allowed many people to access healthcare from the comfort of their homes. Remote follow-up and monitoring are also provided through Telemedicine as postoperative care. The possible scope and application of Artificial Intelligence techniques in the Telehealth area are discussed in this paper. The paper also focuses on different computational solutions involving machine learning and Artificial Intelligence to tackle the crisis. The methods focus on two major areas: 1) improvement in the quality of existing clinical practices, and service delivery. 2) the growth besides the support of innovative models for healthcare. The methods to improve quality include digital storage of patient data and large datasets, automation of manual tasks for CT scans, conducting X-rays and handling the emergency, and electronic consultation for diagnosis, treatment, and monitoring of patients. Innovative methods such as ICT and technology such as accelerometers, GPS, gyroscopes, motion sensors, and so on, are used in healthcare.