Cancer Informatics, Journal Year: 2024, Volume and Issue: 23
Published: Jan. 1, 2024
Objectives: This study aims to introduce a prediction model based on machine learning approach as an efficient solution for purposes better prognosis and increase CRC survival. Methods: In the current retrospective study, we used data of 1062 cases analyse establish 5-year The algorithms were develop models, including random Forest, XG-Boost, bagging, logistic regression, support vector machine, artificial neural network, decision tree, K-nearest neighbours. Results: revealed that XG-Boost with AU-ROC 0.906 0.813 internal external conditions gave us insight into predictability generalizability than other algorithms. Conclusion: can be utilised knowledge source implementing intelligent systems assistive tool clinical decision-making in healthcare settings improve survival through various solutions doctors achieve.
Language: Английский