ArticleComputational and mathematical methods in medicine2021
Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble.
Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning (ML) techniques to predict breast cancer in imbalanced datasets: a systematic review.Journal of cancer survivorship : research and practice · 2025Pooled it
- Enhanced prediction of spine surgery outcomes using advanced machine learning techniques and oversampling methods.Health information science and systems · 2025Article
- Ensemble model for neoadjuvant chemotherapy response prediction and treatment sensitivity in TNBC based on DNA replication stress signatures.Scientific reports · 2025Article
- Development and validation of an explainable machine learning model for predicting postoperative pulmonary complications after lung cancer surgery: a machine learning study.EClinicalMedicine · 2025Article
- Unlocking artificial intelligence, machine learning and deep learning to combat therapeutic resistance in metastatic castration-resistant prostate cancer: a comprehensive review.Ecancermedicalscience · 2025Review
- Ensemble machine learning framework for predicting maternal health risk during pregnancy.Scientific reports · 2024Article
- Brain Tumor Classification based on Improved Stacked Ensemble Deep Learning Methods.Asian Pacific journal of cancer prevention : APJCP · 2023Article
- A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study.Journal of medical Internet research · 2023Article
- A Bayesian optimization tunning integrated multi-stacking classifier framework for the prediction of radiodermatitis from 4D-CT of patients underwent breast cancer radiotherapy.Frontiers in oncology · 2023Article
- SVM-DO: identification of tumor-discriminating mRNA signatures via support vector machines supported by Disease Ontology.Turkish journal of biology = Turk biyoloji dergisi · 2023Article
- Non-Fatal Drowning Risk Prediction Based on Stacking Ensemble Algorithm.Children (Basel, Switzerland) · 2022Article
- Bias and Class Imbalance in Oncologic Data-Towards Inclusive and Transferrable AI in Large Scale Oncology Data Sets.Cancers · 2022Review
- Article
- The Application of Artificial Intelligence to Cancer Research: A Comprehensive Guide.Technology in cancer research & treatmentReview
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages of good flexibility and higher generalization performance. To achieve higher quality cancer classification, in this study, the fast correlation-based feature selection (FCBF) method was used to preprocess the data to eliminate irrelevant and redundant features. Then, the classification was carried out in the stacking ensemble learner. A library for support vector machine (LIBSVM),
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.