ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2021
[Establishment of naive Bayes classifier-based risk prediction model for chemotherapyinduced nausea and vomiting].
Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk prediction models for chemotherapy-induced nausea and vomiting: a systematic review and meta-analysis.Frontiers in oncology · 2026Pooled it
- Development and prospective evaluation of a machine learning model to predict vomiting among pediatric cancer and hematopoietic cell transplant patients.BMC cancer · 2025Article
- Construction of an Early Alert System for Intradialytic Hypotension before Initiating Hemodialysis Based on Machine Learning.Kidney diseases (Basel, Switzerland) · 2023Article
- [Aldehyde dehydrogenase 2 rs671 genetic polymorphisms are associated with chemotherapy-induced nausea and vomiting].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2023Article
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Authors and funding
3 authors.
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Abstract
objectiveTo establish a risk prediction model of chemotherapy-induced nausea and vomiting based on naive Bayes classifier.
objectiveWe collected the basic information, treatment protocols and follow-up data from 300 patients receiving chemotherapy in the Oncology Department of Second Xiangya Hospital from July to September, 2020. Correlation analysis was carried out between the potential factors related to nausea and vomiting in the treatment plan and the individual characteristics of the patients. For the two characteristics with a correlation coefficient greater than 0.8, their contribution to the area under curve (AUC) was calculated, and the characteristic with a smaller contribution was removed. The naive Bayes classifier in the machine learning library scikit-learn was used as the prediction model of chemotherapy-induced nausea and vomiting, and 10-fold stratified-shuffled-split cross-validation was used to obtain the final result of the model. The machine learning model was trained using 70% of the samples, and 30% of the samples were used as the test set to assess the performance of the model.
objectiveThe sensitivity of the model for predicting the risk of nausea and vomiting due to acute chemotherapy was 0.83±0.04 (95%
objectiveThe naive Bayes classifier model has a good performance in predicting the risk of chemotherapy-induced nausea and vomiting in Chinese cancer patients.
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