AIMC Topic: Mammography

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An Efficient Lightweight Multi Head Attention Gannet Convolutional Neural Network Based Mammograms Classification.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: This research aims to use deep learning to create automated systems for better breast cancer detection and categorisation in mammogram images, helping medical professionals overcome challenges such as time consumption, feature extraction ...

Using AI to Select Women with Intermediate Breast Cancer Risk for Breast Screening with MRI.

Radiology
Background Combined mammography and MRI screening is not universally accessible for women with intermediate breast cancer risk due to limited MRI resources. Selecting women for MRI by assessing their mammogram may enable more resource-effective scree...

Evaluating the Impact of Changes in Artificial Intelligence-derived Case Scores over Time on Digital Breast Tomosynthesis Screening Outcomes.

Radiology. Artificial intelligence
Purpose To evaluate the change in digital breast tomosynthesis artificial intelligence (DBT-AI) case scores over sequential screenings. Materials and Methods This retrospective review included 21 108 female patients (mean age ± SD, 58.1 years ± 11.5)...

External Validation of a Commercial Artificial Intelligence Algorithm on a Diverse Population for Detection of False Negative Breast Cancers.

Journal of breast imaging
OBJECTIVE: There are limited data on the application of artificial intelligence (AI) on nonenriched, real-world screening mammograms. This work aims to evaluate the ability of AI to detect false negative cancers not detected at the time of screening ...

Potential Impact of an Artificial Intelligence-based Mammography Triage Algorithm on Performance and Workload in a Population-based Screening Sample.

Journal of breast imaging
OBJECTIVE: To evaluate potential screening mammography performance and workload impact using a commercial artificial intelligence (AI)-based triage device in a population-based screening sample.

Automated Breast Density Assessment for Full-Field Digital Mammography and Digital Breast Tomosynthesis.

Cancer prevention research (Philadelphia, Pa.)
Mammographic density is a strong risk factor for breast cancer and is reported clinically as part of Breast Imaging Reporting and Data System (BI-RADS) results issued by radiologists. Automated assessment of density is needed that can be used for bot...

How should artificial intelligence be used in breast screening? Women's reasoning about workflow options.

PloS one
Studies show that breast screening participants are open to artificial intelligence (AI) in breast screening, but hold concerns about AI performance, governance, equitable access, and dependence on technology. Little is known of consumers' views on h...

Comparative analysis of diagnostic performance in mammography: A reader study on the impact of AI assistance.

PloS one
PURPOSE: This study evaluates the impact of artificial intelligence (AI) assistance on the diagnostic performance of radiologists with varying levels of experience in interpreting mammograms in a Malaysian tertiary referral center, particularly in wo...

ClinValAI: A framework for developing Cloud-based infrastructures for the External Clinical Validation of AI in Medical Imaging.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Artificial Intelligence (AI) algorithms showcase the potential to steer a paradigm shift in clinical medicine, especially medical imaging. Concerns associated with model generalizability and biases necessitate rigorous external validation of AI algor...