Research on Prediction Model of Benign and Malignant Breast Cancer Based on Machine Learning
Year: 2024
Type: article
Abstract: This study uses three machine learning models to perform classification analysis on breast cancer data, aiming to improve diagnostic accuracy. After data preprocessing and standardization, the performance of each model was comprehensively evaluated using classification and regression metrics. The results showed that the logistic regression model performed the best, with an accuracy of 0.9825, while SVM and random forest also showed good performance. The classification effects of each model were visualized through ROC curves and confusion matrices, demonstrating that logistic regression has high application value in breast cancer diagnosis.
DOI: 10.70339/0sgcx828
Author: Lu Gan
Institution: Northern Arizona University
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4402942359