Proceedings of the 2024 3rd International Conference on Public Service, Economic Management and Sustainable Development (PESD 2024)

Machine Learning Methods in Medical Diagnosis

Authors
Nianci You1, *
1University College London, Crime and Security Science, Department of Crime and Security Science, London, WC1E 6BT, UK
*Corresponding author. Email: zctznyo@ucl.ac.uk
Corresponding Author
Nianci You
Available Online 19 December 2024.
DOI
10.2991/978-94-6463-598-0_53How to use a DOI?
Keywords
“machine learning”; “Medical Diagnosis”; “Artificial Neural Networks (ANNs)”; “Decision Tree and Bayesian Classifier (BC)”
Abstract

Incorrect diagnosis can significantly affect outcome of treatment of a patients, which is often caused by cognitive bias of clinicians. This paper summarises development of three common machine learning methods in medical diagnosis -- Artificial Neural Networks (ANNs), Decision Tree and Bayesian Classifier (BC). Development of novel molecular approach can improve the ability of ANN models to accurately classify cancer subtypes such as Small Round Blue Cell Tumors (SRBCTs). Moreover, new medical equipment such as mass spectrometry can assist ANNs model in analysis of ovarian cancer. In order to achieve higher accuracy of Decision Tree in medical diagnosis, Shouman et al. examined different combination of discretization methods and Decision Tree and found that disequal frequency discretization Gain Ratio Decision Tree achieved highest accuracy. In addition, BC is more interpretable than other two classifier models because it can produce probabilistic outputs of the likelihood of a certain diagnosis or outcome.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 3rd International Conference on Public Service, Economic Management and Sustainable Development (PESD 2024)
Series
Advances in Economics, Business and Management Research
Publication Date
19 December 2024
ISBN
978-94-6463-598-0
ISSN
2352-5428
DOI
10.2991/978-94-6463-598-0_53How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Nianci You
PY  - 2024
DA  - 2024/12/19
TI  - Machine Learning Methods in Medical Diagnosis
BT  - Proceedings of the 2024 3rd International Conference on Public Service, Economic Management and Sustainable Development (PESD 2024)
PB  - Atlantis Press
SP  - 513
EP  - 519
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-598-0_53
DO  - 10.2991/978-94-6463-598-0_53
ID  - You2024
ER  -