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A New Range-based Breast Cancer Prediction Model Using the Bayes' Theorem and Ensemble Learning

Research article (Information Technology And Control, 2022) · cited 13× · AI/ML
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A New Range-based Breast Cancer Prediction Model Using the Bayes' Theorem and Ensemble Learning

Summary

A New Range-based Breast Cancer Prediction Model Using the Bayes' Theorem and Ensemble Learning is a scholarly article[1].

Key Facts

  • A New Range-based Breast Cancer Prediction Model Using the Bayes' Theorem and Ensemble Learning's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). A New Range-based Breast Cancer Prediction Model Using the Bayes' Theorem and Ensemble Learning. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-new-range-based-breast-cancer-prediction-model-using-the-bayes-theorem-and-ensemble-learning
MLA “A New Range-based Breast Cancer Prediction Model Using the Bayes' Theorem and Ensemble Learning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-new-range-based-breast-cancer-prediction-model-using-the-bayes-theorem-and-ensemble-learning.
BibTeX @misc{4ortxyz_a-new-range-based-breast-cancer-prediction-model-using-the-bayes-theorem-and-ensemble-learning_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A New Range-based Breast Cancer Prediction Model Using the Bayes' Theorem and Ensemble Learning}}, year = {2026}, url = {https://4ort.xyz/entity/a-new-range-based-breast-cancer-prediction-model-using-the-bayes-theorem-and-ensemble-learning}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A New Range-based Breast Cancer Prediction Model Using the Bayes' Theorem and Ensemble Learning — https://4ort.xyz/entity/a-new-range-based-breast-cancer-prediction-model-using-the-bayes-theorem-and-ensemble-learning (retrieved 2026-05-24)

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