ArticleGlobal journal of health science2015
Prediction of breast cancer survival through knowledge discovery in databases.
Article in Global journal of health science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predicting breast cancer 5-year survival using machine learning: A systematic review.PloS one · 2021Pooled it
- Bayesian Model Prediction for Breast Cancer Survival: A Retrospective Analysis.European journal of breast health · 2025Article
- Application of machine learning in breast cancer survival prediction using a multimethod approach.Scientific reports · 2024Article
- Article
- The Application and Comparison of Machine Learning Models for the Prediction of Breast Cancer Prognosis: Retrospective Cohort Study.JMIR medical informatics · 2022Article
- Prediction of Breast Cancer Survival by Machine Learning Methods: An Application of Multiple Imputation.Iranian journal of public health · 2021Article
- Machine learning is a valid method for predicting prehospital delay after acute ischemic stroke.Brain and behavior · 2020Article
- Parametric survival model to identify the predictors of breast cancer mortality: An accelerated failure time approach.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2020Article
- Individual-patient prediction of meningioma malignancy and survival using the Surveillance, Epidemiology, and End Results database.NPJ digital medicine · 2020Article
- Development and validation of a predictive model for the diagnosis of solid solitary pulmonary nodules using data mining methods.Journal of thoracic disease · 2019Article
- Prediction of Hemodialysis Timing Based on LVW Feature Selection and Ensemble Learning.Journal of medical systems · 2018Article
- Applying Data Mining Techniques to Extract Hidden Patterns about Breast Cancer Survival in an Iranian Cohort Study.Journal of research in health sciences · 2016Article
- Building predictive models for MERS-CoV infections using data mining techniques.Journal of infection and public healthArticle
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The collection of large volumes of medical data has offered an opportunity to develop prediction models for survival by the medical research community. Medical researchers who seek to discover and extract hidden patterns and relationships among large number of variables use knowledge discovery in databases (KDD) to predict the outcome of a disease. The study was conducted to develop predictive models and discover relationships between certain predictor variables and survival in the context of breast cancer. This study is Cross sectional. After data preparation, data of 22,763 female patients, mean age 59.4 years, stored in the Surveillance Epidemiology and End Results (SEER) breast cancer dataset were analyzed anonymously. IBM SPSS Statistics 16, Access 2003 and Excel 2003 were used in the data preparation and IBM SPSS Modeler 14.2 was used in the model design. Support Vector Machine (SVM) model outperformed other models in the prediction of breast cancer survival. Analysis showed SVM model detected ten important predictor variables contributing mostly to prediction of breast cancer survival. Among important variables, behavior of tumor as the most important variable and stage of malignancy as the least important variable were identified. In current study, applying of the knowledge discovery method in the breast cancer dataset predicted the survival condition of breast cancer patients with high confidence and identified the most important variables participating in breast cancer survival.
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