The Role of Mammographic Breast Area/Microcalcification Cluster Area (BA/MCA) Ratio in the Classification of BI-RADS 4 Lesions: A Step for Development of Artificial Intelligence in Breast Cancer Patients

Conclusion: The increase in the ratio of MCA to BA might have a place in the differentiation of BI-RADS 4 lesions. We foresee that artificial intelligence could also have a place in the classification of BI-RADS lesions with software to be installed on the mammography computer.

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Main Authors: Ibrahim Burak Bahçecioğlu, Şevket Barış Morkavuk, Şebnem Çimen, Müjdat Turan, Gökay Çetinkaya, Mehmet Ali Gülçelik
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:International Journal of Clinical Practice
Online Access:http://dx.doi.org/10.1155/ijcp/3533205
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author Ibrahim Burak Bahçecioğlu
Şevket Barış Morkavuk
Şebnem Çimen
Müjdat Turan
Gökay Çetinkaya
Mehmet Ali Gülçelik
author_facet Ibrahim Burak Bahçecioğlu
Şevket Barış Morkavuk
Şebnem Çimen
Müjdat Turan
Gökay Çetinkaya
Mehmet Ali Gülçelik
author_sort Ibrahim Burak Bahçecioğlu
collection DOAJ
description Conclusion: The increase in the ratio of MCA to BA might have a place in the differentiation of BI-RADS 4 lesions. We foresee that artificial intelligence could also have a place in the classification of BI-RADS lesions with software to be installed on the mammography computer.
format Article
id doaj-art-a68db849746f498c99ecacc83fbb2c24
institution Kabale University
issn 1742-1241
language English
publishDate 2024-01-01
publisher Wiley
record_format Article
series International Journal of Clinical Practice
spelling doaj-art-a68db849746f498c99ecacc83fbb2c242024-12-12T00:00:03ZengWileyInternational Journal of Clinical Practice1742-12412024-01-01202410.1155/ijcp/3533205The Role of Mammographic Breast Area/Microcalcification Cluster Area (BA/MCA) Ratio in the Classification of BI-RADS 4 Lesions: A Step for Development of Artificial Intelligence in Breast Cancer PatientsIbrahim Burak Bahçecioğlu0Şevket Barış Morkavuk1Şebnem Çimen2Müjdat Turan3Gökay Çetinkaya4Mehmet Ali Gülçelik5Department of Surgical OncologyDepartment of Surgical OncologyDepartment of General SurgeryDepartment of General SurgeryDepartment of Surgical OncologyDepartment of Surgical OncologyConclusion: The increase in the ratio of MCA to BA might have a place in the differentiation of BI-RADS 4 lesions. We foresee that artificial intelligence could also have a place in the classification of BI-RADS lesions with software to be installed on the mammography computer.http://dx.doi.org/10.1155/ijcp/3533205
spellingShingle Ibrahim Burak Bahçecioğlu
Şevket Barış Morkavuk
Şebnem Çimen
Müjdat Turan
Gökay Çetinkaya
Mehmet Ali Gülçelik
The Role of Mammographic Breast Area/Microcalcification Cluster Area (BA/MCA) Ratio in the Classification of BI-RADS 4 Lesions: A Step for Development of Artificial Intelligence in Breast Cancer Patients
International Journal of Clinical Practice
title The Role of Mammographic Breast Area/Microcalcification Cluster Area (BA/MCA) Ratio in the Classification of BI-RADS 4 Lesions: A Step for Development of Artificial Intelligence in Breast Cancer Patients
title_full The Role of Mammographic Breast Area/Microcalcification Cluster Area (BA/MCA) Ratio in the Classification of BI-RADS 4 Lesions: A Step for Development of Artificial Intelligence in Breast Cancer Patients
title_fullStr The Role of Mammographic Breast Area/Microcalcification Cluster Area (BA/MCA) Ratio in the Classification of BI-RADS 4 Lesions: A Step for Development of Artificial Intelligence in Breast Cancer Patients
title_full_unstemmed The Role of Mammographic Breast Area/Microcalcification Cluster Area (BA/MCA) Ratio in the Classification of BI-RADS 4 Lesions: A Step for Development of Artificial Intelligence in Breast Cancer Patients
title_short The Role of Mammographic Breast Area/Microcalcification Cluster Area (BA/MCA) Ratio in the Classification of BI-RADS 4 Lesions: A Step for Development of Artificial Intelligence in Breast Cancer Patients
title_sort role of mammographic breast area microcalcification cluster area ba mca ratio in the classification of bi rads 4 lesions a step for development of artificial intelligence in breast cancer patients
url http://dx.doi.org/10.1155/ijcp/3533205
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