Applications of Artificial intelligence in the assessment of breast imaging

Artificial intelligence helps doctors and researchers of diagnostic imaging through higher sensitivity and specificity in diagnosis, most importantly, by avoiding wrong positive and negative findings.The purpose of the article is to explain how to enhance 'diagnostic confidence' in imaging diagnosis of nipple lesions to tell the difference between benign and malignant lesions.The article presents the projects and the technology of the AI hybridization with the current mammography, MRI, and ultrasound devices.The development prospects and challenges, encompassing ethical and evolutionary considerations, along with validation and scaling issues, for solutions widely adopted in imaging diagnostics of highlighted breast lesions.

Authors

Publication Details

Journal
Medical Science
Published
2025-05-30
DOI
https://doi.org/10.54905/disssi.v29i158.e69ms3574
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

Applications of Artificial intelligence in the assessment of breast imaging

Agnieszka Waszczuk, Anna Tokarska, Joanna Rybak, Aleksandra Arnista et al.
Medical Science
Radiomics and Machine Learning in Medical Imaging
article

Applications of Artificial intelligence in the assessment of breast imaging

Agnieszka Waszczuk, Anna Tokarska, Joanna Rybak, Aleksandra Arnista, Mateusz Świątko, Katarzyna Gawrońska, Piotr Łapiński, Marcin Grzebyk, Paweł Sosnowski, Aleksandra Kołodziejczyk
article en

Abstract

Artificial intelligence helps doctors and researchers of diagnostic imaging through higher sensitivity and specificity in diagnosis, most importantly, by avoiding wrong positive and negative findings.The purpose of the article is to explain how to enhance 'diagnostic confidence' in imaging diagnosis of nipple lesions to tell the difference between benign and malignant lesions.The article presents the projects and the technology of the AI hybridization with the current mammography, MRI, and ultrasound devices.The development prospects and challenges, encompassing ethical and evolutionary considerations, along with validation and scaling issues, for solutions widely adopted in imaging diagnostics of highlighted breast lesions.

Medical ScienceVol. 29(159)
Openalex Percentile: Top 81%
Radiomics and Machine Learning in Medical Imaging
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