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Cited by 323

The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.

A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues

Open access
Shamshirband, Shahab, Fathi, Mahdis, Dehzangi, Abdollah, Chronopoulos, Anthony Theodore, Alinejad-Rokny, Hamid·2021·Journal of Biomedical Informatics

Abstract

In the last few years, the application of Machine Learning approaches like Deep Neural Network (DNN) models have become more attractive in the healthcare system given the rising complexity of the healthcare data. Machine Learning (ML) algorithms provide efficient and effective data analysis models to uncover hidden patterns and other meaningful information from the considerable amount of health data that conventional analytics are not able to discover in a reasonable time. In particular, Deep Learning (DL) techniques have been shown as promising methods in pattern recognition in the healthcare systems. Motivated by this consideration, the contribution of this paper is to investigate the deep learning approaches applied to healthcare systems by reviewing the cutting-edge network architectures, applications, and industrial trends. The goal is first to provide extensive insight into the application of deep learning models in healthcare solutions to bridge deep learning techniques and human healthcare interpretability. And then, to present the existing open challenges and future directions.

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Metadata

Authors
Shamshirband, S., Fathi, M., Dehzangi, A., Chronopoulos, A. T., & Alinejad-Rokny, H.
Venue
Journal of Biomedical Informatics
Publisher
Elsevier BV
Published
2021-01
Volume
113
Pages
103627
ISSN
1532-0464 (ISSN-L)
OpenAlex
W3107335993
Cited by
323
References
73
FWCI
8.76
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues. https://app.cochat.ai/papers/10.1016/j.jbi.2020.103627
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Shamshirband, S., Fathi, M., Dehzangi, A., Chronopoulos, A. T., & Alinejad-Rokny, H. (2021). A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues. Journal of Biomedical Informatics. https://doi.org/10.1016/j.jbi.2020.103627

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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