AIMC Topic: Mammography

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Impact of AI for Digital Breast Tomosynthesis on Breast Cancer Detection and Interpretation Time.

Radiology. Artificial intelligence
Purpose To develop an artificial intelligence (AI) model for the diagnosis of breast cancer on digital breast tomosynthesis (DBT) images and to investigate whether it could improve diagnostic accuracy and reduce radiologist reading time. Materials an...

Machine learning and new insights for breast cancer diagnosis.

The Journal of international medical research
Breast cancer (BC) is the most prominent form of cancer among females all over the world. The current methods of BC detection include X-ray mammography, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography and bre...

Assessing radiologists' and radiographers' perceptions on artificial intelligence integration: opportunities and challenges.

The British journal of radiology
OBJECTIVES: The objective of this study was to evaluate radiologists' and radiographers' opinions and perspectives on artificial intelligence (AI) and its integration into the radiology department. Additionally, we investigated the most common challe...

Mammography-based deep learning model for coronary artery calcification.

European heart journal. Cardiovascular Imaging
AIMS: Mammography, commonly used for breast cancer screening in women, can also predict cardiovascular disease. We developed mammography-based deep learning models for predicting coronary artery calcium (CAC) scores, an established predictor of coron...

AsymMirai: Interpretable Mammography-based Deep Learning Model for 1-5-year Breast Cancer Risk Prediction.

Radiology
Background Mirai, a state-of-the-art deep learning-based algorithm for predicting short-term breast cancer risk, outperforms standard clinical risk models. However, Mirai is a black box, risking overreliance on the algorithm and incorrect diagnoses. ...

A Multi-Task Learning Approach for Segmentation of Breast Arterial Calcifications in Screening Mammograms.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Screening mammogram is a standard and cost-efficient imaging procedure to measure breast cancer risk among 45+ year old women. Quantifying breast arterial calcification (BAC) from screening mammograms is a non-invasive and cost-efficient approach to ...

Integrating AI into Clinical Workflows: A Simulation Study on Implementing AI-aided Same-day Diagnostic Testing Following an Abnormal Screening Mammogram.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Artificial intelligence (AI) shows promise in clinical tasks, yet its integration into workflows remains underexplored. This study proposes an AI-aided same-day diagnostic imaging workup to reduce recall rates following abnormal screening mammograms ...