AI Medical Compendium Topic:
Mammography

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Classification of Benign and Malignant Breast Masses on Mammograms for Large Datasets using Core Vector Machines.

Current medical imaging
BACKGROUND: Breast cancer is one of the most leading causes of cancer deaths among women. Early detection of cancer increases the survival rate of the affected women. Machine learning approaches that are used for classification of breast cancer usual...

A Survey on Machine Learning Algorithms for the Diagnosis of Breast Masses with Mammograms.

Current medical imaging
Breast cancer is leading cancer among women for the past 60 years. There are no effective mechanisms for completely preventing breast cancer. Rather it can be detected at its earlier stages so that unnecessary biopsy can be reduced. Although there ar...

[New Trends in Breast Imaging].

Therapeutische Umschau. Revue therapeutique
New Trends in Breast Imaging The examination of the breast, especially as a screening examination for breast cancer, has so far been carried out primarily by means of mammography and occasionally supplementary ultrasound. These check-ups have become...

Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram.

Advances in experimental medicine and biology
For computer-aided diagnosis (CAD), detection, segmentation, and classification from medical imagery are three key components to efficiently assist physicians for accurate diagnosis. In this chapter, a completely integrated CAD system based on deep l...

[Artificial intelligence in the diagnosis of breast cancer : Yesterday, today and tomorrow].

Der Radiologe
BACKGROUND: Artificial intelligence (AI) is increasingly applied in the field of breast imaging.

Can a Machine Learn from Radiologists' Visual Search Behaviour and Their Interpretation of Mammograms-a Deep-Learning Study.

Journal of digital imaging
Visual search behaviour and the interpretation of mammograms have been studied for errors in breast cancer detection. We aim to ascertain whether machine-learning models can learn about radiologists' attentional level and the interpretation of mammog...

Comprehensive Word-Level Classification of Screening Mammography Reports Using a Neural Network Sequence Labeling Approach.

Journal of digital imaging
Radiology reports contain a large amount of potentially valuable unstructured data. Recently, neural networks have been employed to perform classification of radiology reports over a few classes at the document level. The success of neural networks i...