Abstract
The COVID-19 has changed the scenario of patient care in most of the hospitals and healthcare centers throughout the world. Since pandemic is spread through contact with the COVID infected person, the most vulnerable community is doctors and healthcare workers. To avoid the mixing of COVID patients from other diseases, there is a need to be a separation, which will contain the spread of virus. As such, remote patient monitoring becomes very essential to take care of the patients under such situations. Because of this medical data is growing exponentially and needs to be analyzed continuously to improve the health care. Data analytics improved the performance of health care organization by proper decision making, accurate and timely information. Medical data can be explored from the sensors or medical equipments installed in the hospitals or can be collected from the fast-growing Internet of Things (IoT) devices. Visualizing the data and correlating the same with the patient monitoring for better treatment and health care is an essential part of it. This paper discusses various Machine Learning (ML) approaches for remote patient monitoring using medical IoT data for the Post-COVID patient care.
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Rahman, S., Parveen, S., Sofi, S.A. (2022). Medical IoT Data Analytics for Post-COVID Patient Monitoring. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Bestak, R. (eds) Expert Clouds and Applications. Lecture Notes in Networks and Systems, vol 444. Springer, Singapore. https://doi.org/10.1007/978-981-19-2500-9_42
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DOI: https://doi.org/10.1007/978-981-19-2500-9_42
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