Cancer Metastasis Prediction and Genomic Biomarker Identification through Machine Learning and eXplainable Artificial Intelligence in Breast Cancer Research

Cancer Metastasis Prediction and Genomic Biomarker Identification through Machine Learning and eXplainable Artificial Intelligence in Breast Cancer Research

Aim: Method: This research presents a model combining machine learning (ML) techniques and eXplainable artificial intelligence (XAI) to predict breast cancer (BC) metastasis and reveal important genomic biomarkers in metastasis patients. Method: A total of 98 primary BC samples was analyzed, compris...

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Bibliographic Details
Main Authors: Burak Yagin, Fatma Hilal Yagin, Cemil Colak, Feyza Inceoglu, Seifedine Kadry, Jungeun Kim
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Diagnostics
Subjects:
breast cancer metastasis
machine learning algorithms
genomic biomarkers
eXplainable artificial intelligence
SHAP
Online Access:https://www.mdpi.com/2075-4418/13/21/3314

Internet

https://www.mdpi.com/2075-4418/13/21/3314

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