AI Medical Compendium Topic

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Mammography

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Towards precision medicine in breast imaging: A novel open mammography database with tailor-made 3D image retrieval for AI and teaching.

Computer methods and programs in biomedicine
This project addresses the global challenge of breast cancer, particularly in low-resource settings, by creating a pioneering mammography database. Breast cancer, identified by the World Health Organization as a leading cause of cancer death among wo...

Clinical Integration of Artificial Intelligence for Breast Imaging.

Radiologic clinics of North America
This article describes an approach to planning and implementing artificial intelligence products in a breast screening service. It highlights the importance of an in-depth understanding of the end-to-end workflow and effective project planning by a m...

Diagnostic capabilities of artificial intelligence as an additional reader in a breast cancer screening program.

European radiology
OBJECTIVES: We aimed to evaluate the early-detection capabilities of AI in a screening program over its duration, with a specific focus on the detection of interval cancers, the early detection of cancers with the assistance of AI from prior visits, ...

Dual view deep learning for enhanced breast cancer screening using mammography.

Scientific reports
Breast cancer has the highest incidence rate among women in Ethiopia compared to other types of cancer. Unfortunately, many cases are detected at a stage where a cure is delayed or not possible. To address this issue, mammography-based screening is w...

Classification performance bias between training and test sets in a limited mammography dataset.

PloS one
OBJECTIVES: To assess the performance bias caused by sampling data into training and test sets in a mammography radiomics study.

Quantitative evaluation of Saliency-Based Explainable artificial intelligence (XAI) methods in Deep Learning-Based mammogram analysis.

European journal of radiology
BACKGROUND: Explainable Artificial Intelligence (XAI) is prominent in the diagnostics of opaque deep learning (DL) models, especially in medical imaging. Saliency methods are commonly used, yet there's a lack of quantitative evidence regarding their ...

Deep learning for computer-aided abnormalities classification in digital mammogram: A data-centric perspective.

Current problems in diagnostic radiology
Breast cancer is the most common type of cancer in women, and early abnormality detection using mammography can significantly improve breast cancer survival rates. Diverse datasets are required to improve the training and validation of deep learning ...

Prediction of Disease-Free Survival in Breast Cancer using Deep Learning with Ultrasound and Mammography: A Multicenter Study.

Clinical breast cancer
BACKGROUND: Breast cancer is a leading cause of cancer morbility and mortality in women. The possibility of overtreatment or inappropriate treatment exists, and methods for evaluating prognosis need to be improved.

Artificial Intelligence for Breast Cancer Detection on Mammography: Factors Related to Cancer Detection.

Academic radiology
RATIONALE AND OBJECTIVES: Little is known about the factors affecting the Artificial Intelligence (AI) software performance on mammography for breast cancer detection. This study was to identify factors associated with abnormality scores assigned by ...