Radiomics-Based Machine Learning Models for Classifying Breast Cancer on Dynamic-Contrast Enhanced MRI through Multi-Observer Analysis

This study demonstrates the potential of integrating radiomic features with ML for breast cancer classification. CatBoost exhibited the highest predictive performance, highlighting its effectiveness in distinguishing malignant from benign lesions.

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Publication Details

Journal
Current Medical Imaging Formerly Current Medical Imaging Reviews
Published
2026-03-03
DOI
https://doi.org/10.2174/0115734056403426251205212737
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Radiomics-Based Machine Learning Models for Classifying Breast Cancer on Dynamic-Contrast Enhanced MRI through Multi-Observer Analysis

Muhammad Khalis Abdul Karim, Faikah Awang Ismail, I. Kamal, M. M. Awang Kechik et al.
Current Medical Imaging Formerly Current Medical Imaging Reviews
Radiomics and Machine Learning in Medical Imaging
article

Radiomics-Based Machine Learning Models for Classifying Breast Cancer on Dynamic-Contrast Enhanced MRI through Multi-Observer Analysis

Muhammad Khalis Abdul Karim, Faikah Awang Ismail, I. Kamal, M. M. Awang Kechik, Erliananiza Mohd Salim, Zahurin Ismail, Kaltham Abdulwahid Noor
article en

Abstract

This study demonstrates the potential of integrating radiomic features with ML for breast cancer classification. CatBoost exhibited the highest predictive performance, highlighting its effectiveness in distinguishing malignant from benign lesions.

Current Medical Imaging Formerly Current Medical Imaging ReviewsVol. 22
Ministry of Health (MY), Dubai Health Authority (AE), Universiti Putra Malaysia (MY), Rashid Hospital (AE), Department of Statistics Malaysia (MY), Universiti Teknologi MARA (MY)
Good health and well-being
Openalex Percentile: Top 26%
Radiomics and Machine Learning in Medical Imaging
DOISourceOpenAlex
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Radiomics-Based Machine Learning Models for Classifying Breast Cancer on Dynamic-Contrast Enhanced MRI through Multi-Observer Analysis — Muhammad Khalis Abdul Karim, Faikah Awang Ismail, et al. · Current Medical Imaging Formerly Current Medical Imaging Reviews (2026) | TGRS Research Map | TGRS