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Applications of Machine Learning in Healthcare and Internet of Things (IOT): A Comprehensive Review

arXiv 2202.02868 ↗First posted 6 Feb 2022cs.LG cs.CYcited by 0

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Abstract (arXiv)

In recent years, smart healthcare IoT devices have become ubiquitous, but they work in isolated networks due to their policy. Having these devices connected in a network enables us to perform medical distributed data analysis. However, the presence of diverse IoT devices in terms of technology, structure, and network policy, makes it a challenging issue while applying traditional centralized learning algorithms on decentralized data collected from the IoT devices. In this study, we present an extensive review of the state-of-the-art machine learning applications particularly in healthcare, challenging issues in IoT, and corresponding promising solutions. Finally, we highlight some open-ended issues of IoT in healthcare that leaves further research studies and investigation for scientists.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 27 of its 108 references that are in the map. First posted on arXiv 6 Feb 2022.

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27 of 108 references.

References · 27

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15 more
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