Table_1_Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.docx

Table_1_Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.docx

Objective<p>This study was conducted in order to investigate the feasibility of using radiomics analysis (RA) with machine learning algorithms based on breast magnetic resonance (MR) images for discriminating malignant from benign MR-detected additional lesions in patients with primary breast...

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Main Author: Hyo-jae Lee (11780051) (author)
Other Authors: Anh-Tien Nguyen (11780054) (author), So Yeon Ki (11780057) (author), Jong Eun Lee (8601699) (author), Luu-Ngoc Do (11780060) (author), Min Ho Park (646582) (author), Ji Shin Lee (11780063) (author), Hye Jung Kim (8308458) (author), Ilwoo Park (4782501) (author), Hyo Soon Lim (11780066) (author)
Published: 2021
Subjects:
Cancer
Cancer Cell Biology
Cancer Diagnosis
Cancer Genetics
Cancer Therapy (excl. Chemotherapy and Radiation Therapy)
Chemotherapy
Haematological Tumours
Molecular Targets
Radiation Therapy
Solid Tumours
Oncology and Carcinogenesis not elsewhere classified
breast neoplasms
magnetic resonance imaging
machine learning
radiomics
ultrasonography
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