دورية أكاديمية

Gradient-Boosting Algorithm for Microwave Breast Lesion Classification—SAFE Clinical Investigation

التفاصيل البيبلوغرافية
العنوان: Gradient-Boosting Algorithm for Microwave Breast Lesion Classification—SAFE Clinical Investigation
المؤلفون: Aleksandar Janjic, Ibrahim Akduman, Mehmet Cayoren, Onur Bugdayci, Mustafa Erkin Aribal
المصدر: Diagnostics, Vol 12, Iss 12, p 3151 (2022)
بيانات النشر: MDPI AG, 2022.
سنة النشر: 2022
المجموعة: LCC:Medicine (General)
مصطلحات موضوعية: microwave breast imaging (MBI), SAFE, breast lesion classification, machine learning, Medicine (General), R5-920
الوصف: (1) Background: Microwave breast imaging (MBI) is a promising breast-imaging technology that uses harmless electromagnetic waves to radiate the breast and assess its internal structure. It utilizes the difference in dielectric properties of healthy and cancerous tissue, as well as the dielectric difference between different cancerous tissue types to identify anomalies inside the breast and make further clinical predictions. In this study, we evaluate the capability of our upgraded MBI device to provide breast tissue pathology. (2) Methods: Only patients who were due to undergo biopsy were included in the study. A machine learning (ML) approach, namely Gradient Boosting, was used to understand information from the frequency spectrum, collected via SAFE, and provide breast tissue pathology. (3) Results: A total of 54 patients were involved in the study: 29 of them had benign and 25 had malignant findings. SAFE acquired 20 true-positive, 24 true-negative, 4 false-positive and 4 false-negative findings, achieving the sensitivity, specificity and accuracy of 80%, 83% and 81%, respectively. (4) Conclusions: The use of harmless tissue radiation indicates that SAFE can be used to provide the breast pathology of women of any age without safety restrictions. Results indicate that SAFE is capable of providing breast pathology at a high rate, encouraging further clinical investigations.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2075-4418
العلاقة: https://www.mdpi.com/2075-4418/12/12/3151Test; https://doaj.org/toc/2075-4418Test
DOI: 10.3390/diagnostics12123151
الوصول الحر: https://doaj.org/article/ef1afeff41df436c88df5ff40419b7acTest
رقم الانضمام: edsdoj.f1afeff41df436c88df5ff40419b7ac
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20754418
DOI:10.3390/diagnostics12123151