AIMC Topic: Mammography
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Artificial intelligence in mammography: a systematic review of the external validation.
Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia
Sep 4, 2024
OBJECTIVE: To conduct a systematic review of external validation studies on the use of different Artificial Intelligence algorithms in breast cancer screening with mammography.
Cost-Effectiveness of AI for Risk-Stratified Breast Cancer Screening.
JAMA network open
Sep 3, 2024
IMPORTANCE: Previous research has shown good discrimination of short-term risk using an artificial intelligence (AI) risk prediction model (Mirai). However, no studies have been undertaken to evaluate whether this might translate into economic gains.
Deep Location Soft-Embedding-Based Network With Regional Scoring for Mammogram Classification.
IEEE transactions on medical imaging
Sep 3, 2024
Early detection and treatment of breast cancer can significantly reduce patient mortality, and mammogram is an effective method for early screening. Computer-aided diagnosis (CAD) of mammography based on deep learning can assist radiologists in makin...
Mammography classification with multi-view deep learning techniques: Investigating graph and transformer-based architectures.
Medical image analysis
Sep 2, 2024
The potential and promise of deep learning systems to provide an independent assessment and relieve radiologists' burden in screening mammography have been recognized in several studies. However, the low cancer prevalence, the need to process high-re...
Comparison of AI-integrated pathways with human-AI interaction in population mammographic screening for breast cancer.
Nature communications
Aug 30, 2024
Artificial intelligence (AI) readers of mammograms compare favourably to individual radiologists in detecting breast cancer. However, AI readers cannot perform at the level of multi-reader systems used by screening programs in countries such as Austr...
An optimal fast fractal method for breast masses diagnosis using machine learning.
Medical engineering & physics
Aug 23, 2024
This article introduces a fast fractal method for classifying breast cancerous lesions in mammography. While fractal methods are valuable for extracting information, they often come with a high computational load and time consumption. This paper demo...
An optimized model based on adaptive convolutional neural network and grey wolf algorithm for breast cancer diagnosis.
PloS one
Aug 19, 2024
Medical image classification (IC) is a method for categorizing images according to the appropriate pathological stage. It is a crucial stage in computer-aided diagnosis (CAD) systems, which were created to help radiologists with reading and analyzing...
Simulation training in mammography with AI-generated images: a multireader study.
European radiology
Aug 12, 2024
OBJECTIVES: The interpretation of mammograms requires many years of training and experience. Currently, training in mammography, like the rest of diagnostic radiology, is through institutional libraries, books, and experience accumulated over time. W...
Simulated arbitration of discordance between radiologists and artificial intelligence interpretation of breast cancer screening mammograms.
Journal of medical screening
Aug 11, 2024
Artificial intelligence (AI) algorithms have been retrospectively evaluated as replacement for one radiologist in screening mammography double-reading; however, methods for resolving discordance between radiologists and AI in the absence of 'real-wor...
Impact of Downsampling Size and Interpretation Methods on Diagnostic Accuracy in Deep Learning Model for Breast Cancer Using Digital Breast Tomosynthesis Images.
The Tohoku journal of experimental medicine
Jul 25, 2024
While deep learning (DL) models have shown promise in breast cancer diagnosis using digital breast tomosynthesis (DBT) images, the impact of varying matrix sizes and image interpolation methods on diagnostic accuracy remains unclear. Understanding th...
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