Methods for Clinical Disease Classification and Clustering: A Review

Yong Shuai, Yong Shuai, Xiaoxia Dai, Xiaoxia Dai, Xiaodong Wang, Zeshan Liang, Zeshan Liang, Gang Yan, Gang Yan, Ming Chen, Ming Chen

2022

Abstract

The appropriate use of accurate clinical classification is of great importance for appropriate clinical diagnosis, treatment, and for meaningful clinical research. Current clinical classification methods lack unified norms and methods in feature selection, number of classification, and classification methods. It has thus become necessary to discuss and critique current methods of clinical classification, and to discuss and formulate constructive opinions regarding clinical classification in the future. We conducted a literature review of open source references containing predetermined terms published in Chinese and English from 2003 to 2021. Our search retrieved 59 studies concerning classification methods among different diseases. General processes, feature selection, and classification methods of clinical classification were then summarized and analyzed. The existing problems of current literature in clinical classification data sources, feature selection, number of classification, and methods were analyzed. We then propose targeted measures with respect to these problems, to help researchers find a suitable method for classification. Through a literature review, we have discovered the shortcomings of current clinical classification methods, and herein suggest corresponding countermeasures. We hope to improve the scientific basis of future classification methods and the interpretability of classification results by implementation of the countermeasures proposed in this review, so that classification results can be more universally recognized, and used over a wider range.

Paper Citation

in Harvard Style

Shuai Y., Dai X., Wang X., Liang Z., Yan G. and Chen M. (2022). Methods for Clinical Disease Classification and Clustering: A Review. In Proceedings of the 4th International Conference on Biotechnology and Biomedicine - Volume 1: ICBB; ISBN 978-989-758-637-8, SciTePress, pages 116-124. DOI: 10.5220/0012014700003633

in Bibtex Style

@conference{icbb22,
author={Yong Shuai and Xiaoxia Dai and Xiaodong Wang and Zeshan Liang and Gang Yan and Ming Chen},
title={Methods for Clinical Disease Classification and Clustering: A Review},
booktitle={Proceedings of the 4th International Conference on Biotechnology and Biomedicine - Volume 1: ICBB},
year={2022},
pages={116-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012014700003633},
isbn={978-989-758-637-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Biotechnology and Biomedicine - Volume 1: ICBB
TI - Methods for Clinical Disease Classification and Clustering: A Review
SN - 978-989-758-637-8
AU - Shuai Y.
AU - Dai X.
AU - Wang X.
AU - Liang Z.
AU - Yan G.
AU - Chen M.
PY - 2022
SP - 116
EP - 124
DO - 10.5220/0012014700003633
PB - SciTePress