Artificial intelligence in breast imaging

EPV Le, Y Wang, Y Huang, S Hickman, FJ Gilbert - Clinical radiology, 2019 - Elsevier
This article reviews current limitations and future opportunities for the application of
computer-aided detection (CAD) systems and artificial intelligence in breast imaging …

Supplemental screening for breast cancer in women with dense breasts: a systematic review for the US Preventive Services Task Force

J Melnikow, JJ Fenton, EP Whitlock… - Annals of internal …, 2016 - acpjournals.org
Background: Screening mammography has lower sensitivity and specificity in women with
dense breasts, who experience higher breast cancer risk. Purpose: To perform a systematic …

[HTML][HTML] BreastScreening-AI: Evaluating medical intelligent agents for human-AI interactions

FM Calisto, C Santiago, N Nunes… - Artificial Intelligence in …, 2022 - Elsevier
In this paper, we developed BreastScreening-AI within two scenarios for the classification of
multimodal beast images:(1) Clinician-Only; and (2) Clinician-AI. The novelty relies on the …

[HTML][HTML] Volumetric breast density affects performance of digital screening mammography

JOP Wanders, K Holland, WB Veldhuis… - Breast cancer research …, 2017 - Springer
Purpose To determine to what extent automatically measured volumetric mammographic
density influences screening performance when using digital mammography (DM). Methods …

Intra‐and interreader reproducibility of PI‐RADSv2: A multireader study

CP Smith, SA Harmon, T Barrett… - Journal of Magnetic …, 2019 - Wiley Online Library
Background The Prostate Imaging Reporting and Data System version 2 (PI‐RADSv2) has
been in use since 2015; while interreader reproducibility has been studied, there has been a …

[HTML][HTML] Artificial intelligence in breast cancer diagnosis and personalized medicine

JS Ahn, S Shin, SA Yang, EK Park, KH Kim… - Journal of Breast …, 2023 - ncbi.nlm.nih.gov
Breast cancer is a significant cause of cancer-related mortality in women worldwide. Early
and precise diagnosis is crucial, and clinical outcomes can be markedly enhanced. The rise …

[HTML][HTML] Errors in mammography cannot be solved through technology alone

EU Ekpo, M Alakhras, P Brennan - Asian Pacific journal of cancer …, 2018 - ncbi.nlm.nih.gov
Mammography has been the frontline screening tool for breast cancer for decades.
However, high error rates in the form of false negatives (FNs) and false positives (FPs) have …

Breast density, benign breast disease, and risk of breast cancer over time

M Román, J Louro, M Posso, R Alcántara, L Peñalva… - European …, 2021 - Springer
Objectives Assessing the combined effect of mammographic density and benign breast
disease is of utmost importance to design personalized screening strategies. Methods We …

Inaccurate labels in weakly-supervised deep learning: Automatic identification and correction and their impact on classification performance

D Hao, L Zhang, J Sumkin… - IEEE journal of …, 2020 - ieeexplore.ieee.org
In data-driven deep learning-based modeling, data quality may substantially influence
classification performance. Correct data labeling for deep learning modeling is critical. In …

Breast density: clinical implications and assessment methods

NS Winkler, S Raza, M Mackesy, RL Birdwell - Radiographics, 2015 - pubs.rsna.org
Breast density assessment is an important component of the screening mammography
report and conveys information to referring clinicians about mammographic sensitivity and …