Trends in Using IoT with Machine Learning in Health Prediction System

被引:50
作者
Aldahiri, Amani [1 ]
Alrashed, Bashair [1 ]
Hussain, Walayat [2 ]
机构
[1] Univ Jeddah, Coll Comp Sci & Engn, Dept Cybersecur, Jeddah 21589, Saudi Arabia
[2] Univ Technol Sydney, Fac Engn & Informat Technol, Sch Informat Syst & Modelling, Sydney, NSW 2007, Australia
来源
FORECASTING | 2021年 / 3卷 / 01期
关键词
IoT; ML; health prediction system; classification; prediction; supervised learning; NEURAL-NETWORKS; CARE; FRAMEWORK;
D O I
10.3390/forecast3010012
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Machine learning (ML) is a powerful tool that delivers insights hidden in Internet of Things (IoT) data. These hybrid technologies work smartly to improve the decision-making process in different areas such as education, security, business, and the healthcare industry. ML empowers the IoT to demystify hidden patterns in bulk data for optimal prediction and recommendation systems. Healthcare has embraced IoT and ML so that automated machines make medical records, predict disease diagnoses, and, most importantly, conduct real-time monitoring of patients. Individual ML algorithms perform differently on different datasets. Due to the predictive results varying, this might impact the overall results. The variation in prediction results looms large in the clinical decision-making process. Therefore, it is essential to understand the different ML algorithms used to handle IoT data in the healthcare sector. This article highlights well-known ML algorithms for classification and prediction and demonstrates how they have been used in the healthcare sector. The aim of this paper is to present a comprehensive overview of existing ML approaches and their application in IoT medical data. In a thorough analysis, we observe that different ML prediction algorithms have various shortcomings. Depending on the type of IoT dataset, we need to choose an optimal method to predict critical healthcare data. The paper also provides some examples of IoT and machine learning to predict future healthcare system trends.
引用
收藏
页码:181 / 206
页数:26
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