Smart Healthcare: Using IoT and Machine Learning-Based Analytics

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Abstract

Smart medicinal services is an inventive procedure of synergizing the advantages of sensors, Internet of things (IoT), and large information Analytics to convey improved patient consideration while lessening the human services costs. The Medical Services industry faces tremendous difficulties to spare the information produced and to process it to separate information out of it. The expanding volume of human services information created through IoT gadgets, electronic health, mobile health, and telemedicine screening requires the advancement of new strategies and approaches for their taking care of. In this chapter, we discuss a portion of the healthcare challenges and information analysis development. To screen the health status of an individual, support from sensors and IoT gadgets is fundamental. The goal of this examination is to give healthcare services administrations to the sick just as sound populace through remote observation utilizing keen calculations, instruments, and methods with quicker investigation and master intervention for better treatment suggestions. The analysis is done on the Blood Pressure data and Heart Disease dataset by collecting the data from the IoT sensors and the framework is able to predict the disease. It can likewise be gainful for distantly checking chronic diseases, which require essential physical data, biological, and hereditary information.

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APA

Sunagar, P., Hanumantharaju, R., Pradeep Kumar, D., Sowmya, B. J., Seema, S., & Kanavalli, A. (2021). Smart Healthcare: Using IoT and Machine Learning-Based Analytics. In Studies in Big Data (Vol. 88, pp. 307–329). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-0415-7_15

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