AIMC Topic: Mammography
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Analyzing Geospatial and Socioeconomic Disparities in Breast Cancer Screening Among Populations in the United States: Machine Learning Approach.
JMIR cancer
Jan 16, 2025
BACKGROUND: Breast cancer screening plays a pivotal role in early detection and subsequent effective management of the disease, impacting patient outcomes and survival rates.
Healthcare Disparities
Spatial Analysis
Social Determinants of Health
Behavioral Risk Factor Surveillance System
Socioeconomic Disparities in Health
Mass Screening
Machine Learning
Early Detection of Cancer
Middle Aged
Mammography
United States
Female
Socioeconomic Factors
Aged
Breast Neoplasms
Humans
Attention-guided erasing for enhanced transfer learning in breast abnormality classification.
International journal of computer assisted radiology and surgery
Jan 15, 2025
PURPOSE: Breast cancer remains one of the most prevalent cancers globally, necessitating effective early screening and diagnosis. This study investigates the effectiveness and generalizability of our recently proposed data augmentation technique, att...
AI image analysis as the basis for risk-stratified screening.
Japanese journal of radiology
Jan 11, 2025
Artificial intelligence (AI) has emerged as a transformative tool in breast cancer screening, with two distinct applications: computer-aided cancer detection (CAD) and risk prediction. While AI CAD systems are slowly finding its way into clinical pra...
A Radiomic-Clinical Model of Contrast-Enhanced Mammography for Breast Cancer Biopsy Outcome Prediction.
Academic radiology
Jan 10, 2025
RATIONALE AND OBJECTIVES: In the USA over 1 million breast biopsies are performed annually. Approximately 9.6% diagnostic exams were given Breast Imaging Reporting and Data System (BI-RADS) ≥4A, most of which are 4A/4B. Contrast-enhanced mammography ...
Traditional versus modern approaches to screening mammography: a comparison of computer-assisted detection for synthetic 2D mammography versus an artificial intelligence algorithm for digital breast tomosynthesis.
Breast cancer research and treatment
Jan 9, 2025
PURPOSE: Traditional computer-assisted detection (CADe) algorithms were developed for 2D mammography, while modern artificial intelligence (AI) algorithms can be applied to 2D mammography and/or digital breast tomosynthesis (DBT). The objective is to...
Nationwide real-world implementation of AI for cancer detection in population-based mammography screening.
Nature medicine
Jan 7, 2025
Artificial intelligence (AI) in mammography screening has shown promise in retrospective evaluations, but few prospective studies exist. PRAIM is an observational, multicenter, real-world, noninferiority, implementation study comparing the performanc...
DIFLF: A domain-invariant features learning framework for single-source domain generalization in mammogram classification.
Computer methods and programs in biomedicine
Jan 6, 2025
BACKGROUND AND OBJECTIVE: Single-source domain generalization (SSDG) aims to generalize a deep learning (DL) model trained on one source dataset to multiple unseen datasets. This is important for the clinical applications of DL-based models to breast...
Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning.
Radiological physics and technology
Jan 6, 2025
Self-supervised learning (SSL) has gained attention in the medical field as a deep learning approach utilizing unlabeled data. The Jigsaw puzzle task in SSL enables models to learn both features of images and the positional relationships within image...
Longitudinal interpretability of deep learning based breast cancer risk prediction.
Physics in medicine and biology
Dec 24, 2024
Deep-learning-based models have achieved state-of-the-art breast cancer risk (BCR) prediction performance. However, these models are highly complex, and the underlying mechanisms of BCR prediction are not fully understood. Key questions include wheth...
Artificial intelligence-based computer-aided diagnosis for breast cancer detection on digital mammography in Hong Kong.
Hong Kong medical journal = Xianggang yi xue za zhi
Dec 19, 2024
INTRODUCTION: Research concerning artificial intelligence in breast cancer detection has primarily focused on population screening. However, Hong Kong lacks a population-based screening programme. This study aimed to evaluate the potential of artific...
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