Machine Learning-Driven Internet of Things (MLIoT)-Based Healthcare Monitoring System

View Sample PDF

Author(s): Kutubuddin Sayyad Liyakat Kazi (Brahmdevdada Mane Institute of Technology, India)and Mahesh Ashok Mahant (Walchand Institute of Technology, India)
Copyright: 2025
Pages: 32
Source title: Digitalization and the Transformation of the Healthcare Sector
Source Author(s)/Editor(s): Nilmini Wickramasinghe (La Trobe University, Australia)
DOI: 10.4018/979-8-3693-9641-4.ch007

Keywords: Medical Information Science Reference / Medical Technologies / Medicine & Healthcare

Purchase

View Machine Learning-Driven Internet of Things (MLIoT)-Based Healthcare Monitoring System on the publisher's website for pricing and purchasing information.

Abstract

Healthcare organisations frequently use Machine Learning(ML) to generate precise and timely results. Doctors can make preliminary choices to save patients' lives thanks to early disease predictions. The power of Machine Learning(ML) applications in healthcare is being increased thanks in part to IoT- Internet of Things. ML-Machine learning techniques are utilised to analyse the data collected from IoT sensors about patients. The principal objective of the endeavour is to develop ML-based healthcare Framework that can reliably and early identify various diseases. Adaptive boosting, Random Forest, Decision Trees, Support Vector Machines, Naïve Bayes, Artificial Neural Networks & K-Nearest Neighbor are seven ML classification algorithms used in this work to predict nine fatal diseases: Blood Pressure, Diabetes, Hepatitis, and Kidney Disorders. The performance metrics—likes Accuracy, Precision, and Recall stand used to assess effectiveness of suggested model.

The IRMA Community

Research IRM

Machine Learning-Driven Internet of Things (MLIoT)-Based Healthcare Monitoring System

Purchase

Abstract

Related Content

IRMA Sponsors