Trends in using IoT with machine learning in health prediction system
Journal article
Aldahiri, Amani, Alrashed, Bashair and Hussain, Walayat. (2021). Trends in using IoT with machine learning in health prediction system. Forecasting. 3(1), pp. 181-206. https://doi.org/10.3390/forecast3010012
Authors | Aldahiri, Amani, Alrashed, Bashair and Hussain, Walayat |
---|---|
Abstract | 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. |
Keywords | IoT; ML; health prediction system; classification; prediction; supervised learning |
Year | 2021 |
Journal | Forecasting |
Journal citation | 3 (1), pp. 181-206 |
Publisher | Multidisciplinary Digital Publishing Institute (MDPI AG) |
ISSN | 2571-9394 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/forecast3010012 |
Scopus EID | 2-s2.0-85109475227 |
Open access | Published as ‘gold’ (paid) open access |
Page range | 181-206 |
Publisher's version | License File Access Level Open |
Output status | Published |
Publication dates | |
Online | 07 Mar 2021 |
Publication process dates | |
Accepted | 03 Mar 2021 |
Deposited | 18 Jul 2023 |
https://acuresearchbank.acu.edu.au/item/8z502/trends-in-using-iot-with-machine-learning-in-health-prediction-system
Download files
Publisher's version
OA_Aldahiri_2021_Trends_in_using_IoT_with_machine.pdf | |
License: CC BY 4.0 | |
File access level: Open |
98
total views25
total downloads0
views this month0
downloads this month