Deep Learning in Healthcare System for Quality of Service.
Journal
Journal of healthcare engineering
ISSN: 2040-2309
Titre abrégé: J Healthc Eng
Pays: England
ID NLM: 101528166
Informations de publication
Date de publication:
2022
2022
Historique:
received:
29
12
2021
accepted:
29
01
2022
entrez:
14
3
2022
pubmed:
15
3
2022
medline:
7
5
2022
Statut:
epublish
Résumé
Deep learning (DL) and machine learning (ML) have a pivotal role in logistic supply chain management and smart manufacturing with proven records. The ability to handle large complex data with minimal human intervention made DL and ML a success in the healthcare systems. In the present healthcare system, the implementation of ML and DL is extensive to achieve a higher quality of service and quality of health to patients, doctors, and healthcare professionals. ML and DL were found to be effective in disease diagnosis, acute disease detection, image analysis, drug discovery, drug delivery, and smart health monitoring. This work presents a state-of-the-art review on the recent advancements in ML and DL and their implementation in the healthcare systems for achieving multi-objective goals. A total of 10 papers have been thoroughly reviewed that presented novel works of ML and DL integration in the healthcare system for achieving various targets. This will help to create reference data that can be useful for future implementation of ML and DL in other sectors of healthcare system.
Identifiants
pubmed: 35281541
doi: 10.1155/2022/8169203
pmc: PMC8906124
doi:
Types de publication
Journal Article
Review
Retracted Publication
Langues
eng
Sous-ensembles de citation
IM
Pagination
8169203Commentaires et corrections
Type : RetractionIn
Informations de copyright
Copyright © 2022 Dibyahash Bordoloi et al.
Déclaration de conflit d'intérêts
The authors declare that there are no conflicts of interest regarding the publication of this study.
Références
Sensors (Basel). 2020 May 13;20(10):
pubmed: 32414205
Wirel Pers Commun. 2021 Aug 21;:1-15
pubmed: 34456513