AIMC Topic: Mammography

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Evaluating Artificial Intelligence Systems to Guide Purchasing Decisions.

Journal of the American College of Radiology : JACR
Many radiologists are considering investments in artificial intelligence (AI) to improve the quality of care for our patients. This article outlines considerations for the purchasing process beginning with performance evaluation. Practices should dec...

Mammographic image classification with deep fusion learning.

Scientific reports
To better address the recognition of abnormalities among mammographic images, in this study we apply the deep fusion learning approach based on Pre-trained models to discover the discriminative patterns between Normal and Tumor categories. We designe...

Computational Radiology in Breast Cancer Screening and Diagnosis Using Artificial Intelligence.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Breast cancer screening has been shown to significantly reduce mortality in women. The increased utilization of screening examinations has led to growing demands for rapid and accurate diagnostic reporting. In modern breast imaging centers, full-fiel...

New convolutional neural network model for screening and diagnosis of mammograms.

PloS one
Breast cancer is the most common cancer in women and poses a great threat to women's life and health. Mammography is an effective method for the diagnosis of breast cancer, but the results are largely limited by the clinical experience of radiologist...

Artificial Intelligence in plastic surgery: What is it? Where are we now? What is on the horizon?

Annals of the Royal College of Surgeons of England
INTRODUCTION: An increasing quantity of data is required to guide precision medicine and advance future healthcare practices, but current analytical methods often become overwhelmed. Artificial intelligence (AI) provides a promising solution. Plastic...

Range of Radiologist Performance in a Population-based Screening Cohort of 1 Million Digital Mammography Examinations.

Radiology
Background There is great interest in developing artificial intelligence (AI)-based computer-aided detection (CAD) systems for use in screening mammography. Comparative performance benchmarks from true screening cohorts are needed. Purpose To determi...

A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Breast cancer is the most frequent cancer in women. The Spanish healthcare network established population-based screening programs in all Autonomous Communities, where mammograms of asymptomatic women are taken with early di...

An Efficient Segmentation and Classification System in Medical Images Using Intuitionist Possibilistic Fuzzy C-Mean Clustering and Fuzzy SVM Algorithm.

Sensors (Basel, Switzerland)
The herpesvirus, polyomavirus, papillomavirus, and retrovirus families are associated with breast cancer. More effort is needed to assess the role of these viruses in the detection and diagnosis of breast cancer cases in women. The aim of this paper ...

The correlation of deep learning-based CAD-RADS evaluated by coronary computed tomography angiography with breast arterial calcification on mammography.

Scientific reports
This study sought to evaluate the association of breast arterial calcification (BAC) on breast screening mammography with the Coronary Artery Disease-Reporting and Data System (CAD-RADS) based on Deep Learning-coronary computed tomography angiography...