research-article

Research on Cancer Diagnosis Method Based on LightGBM-Gridsearchcv

Authors:

Yongtao SongAuthors Info & Claims

BDE '22: Proceedings of the 4th International Conference on Big Data Engineering

Pages 122 - 126

https://doi.org/10.1145/3538950.3538966

Published: 19 July 2022 Publication History

Abstract

Cancer has become a non-negligible problem that threatens human health in today's society. The traditional methods of cancer diagnosis usually use cell morphology, histopathology and other methods. Nowadays, the use of machine learning technology to predict cancer has become a new actionable way. This paper proposes the use of machine learning algorithms to assist breast cancer diagnosis, using a variety of algorithms such as LightGBM, Random Forests (RF), Support Vector Machines (SVM), Linear SVM, K-Nearest Neighbor (KNN), and combined with grid search algorithms, respectively constructed intelligent predictive and diagnostic models for malignant breast cancer. Finally, using the breast cancer data set of the University of Wisconsin (WCBD) hospital to conduct experiments, a classification model based on LightGBM-Gridsearchcv is proposed. Compared with the models, the LightGBM-Gridsearchcv model has a recognition accuracy of 95.9% for malignant cancer cases. The machine learning method has put forward a new research idea and method for the diagnosis of breast cancer, and provided a research direction for the promotion of intelligent medical treatment, which has very important practical significance and application value.

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Cited By

Gupta VSharma R(2024)Enhancing Breast Cancer Prediction with XAI-Enabled Boosting Algorithms2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10723843(1-5)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10723843
Cui CYao XXu LChao YHu YZhao SHu YZhang J(2023)Improving the Classification of PCNSL and Brain Metastases by Developing a Machine Learning Model Based on 18F-FDG PETJournal of Personalized Medicine10.3390/jpm1303053913:3(539)Online publication date: 17-Mar-2023
https://doi.org/10.3390/jpm13030539

Research on Cancer Diagnosis Method Based on LightGBM-Gridsearchcv
1. Computing methodologies

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BDE '22: Proceedings of the 4th International Conference on Big Data Engineering

May 2022

139 pages

ISBN:9781450395632

DOI:10.1145/3538950

Copyright © 2022 ACM.

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Publication History

Published: 19 July 2022

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BDE 2022

BDE 2022: 2022 4th International Conference on Big Data Engineering

May 26 - 28, 2022

Beijing, China

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Cited By

Gupta VSharma R(2024)Enhancing Breast Cancer Prediction with XAI-Enabled Boosting Algorithms2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10723843(1-5)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10723843
Cui CYao XXu LChao YHu YZhao SHu YZhang J(2023)Improving the Classification of PCNSL and Brain Metastases by Developing a Machine Learning Model Based on 18F-FDG PETJournal of Personalized Medicine10.3390/jpm1303053913:3(539)Online publication date: 17-Mar-2023
https://doi.org/10.3390/jpm13030539

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