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Application of Machine Learning in Healthcare IoT: An Investigation on Disease Diagnosis and Analytic Cases
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Author(s): Ashwini Kumar Pradhan (Galgotias University, India), Arvind Yadav (Galgotias University, India), Nilamadhab Mishra (VIT Bhopal University, India), Rudra Kalyan Nayak (VIT Bhopal University, India), Hitesh Mohapatra (KIIT University, India), Lambodar Jena (Shiksha 'O' Anusandhan University, India)and Akhilesh Kumar Tripathi (Galgotias University, India)
Copyright: 2025
Pages: 24
Source title:
Exploration of Transformative Technologies in Healthcare 6.0
Source Author(s)/Editor(s): Piyush Kumar (IILM University, Gurugram, India), Pankaj Rahi (Institute of Health Management and Research, Bangalore, India), S.D. Gupta (Institute of Health Management and Research, Bangalore, India), Kirti Udayai (Max Healthcare Institute Limited, India)and Prashant Singh (Independent Researcher, India)
DOI: 10.4018/979-8-3693-7210-4.ch007
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Abstract
Machine learning (ML) is the most prominent topic, with many applications in video processing, language processing, visual diagnosis of illnesses, drug development, biochemistry, and biomedical. Healthcare systems and medical science-related applications are rapidly growing among these applications. Large data expansion, the Internet of Things (IoT), networked devices, and high-performance computers with graphics processing units are all contributing to the growing popularity of ML. Healthcare in IoT (HIoT), and electronic health record (EHR) data are the key data resources for neural network (NN) models. Several possible challenges, including security and quality of service improvement, are important to ML. Based on the comprehensive literature survey (CLS), ML for HIoT is examined in this research.
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