AIMC Topic: Calcinosis

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Application of deep learning in the detection of breast lesions with four different breast densities.

Cancer medicine Jun 16, 2021
OBJECTIVE: This retrospective study evaluated the model from populations with different breast densities and showed the model's performance on malignancy prediction.
Middle Aged Deep Learning Humans Aged ROC Curve Calcinosis Retrospective Studies Triple Negative Breast Neoplasms Adult Mammography Female Sensitivity and Specificity Breast Density Breast Neoplasms
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Natural Language Processing to Identify Pulmonary Nodules and Extract Nodule Characteristics From Radiology Reports.

Chest Jun 4, 2021
BACKGROUND: There is an urgent need for population-based studies on managing patients with pulmonary nodules.
Lung Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Algorithms Humans Tomography, X-Ray Computed Sensitivity and Specificity Quality Improvement Calcinosis Natural Language Processing Documentation Radiology Radiography, Thoracic Tumor Burden Dimensional Measurement Accuracy
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3D Context-Aware Convolutional Neural Network for False Positive Reduction in Clustered Microcalcifications Detection.

IEEE journal of biomedical and health informatics Mar 5, 2021
False positives (FPs) reduction is indispensable for clustered microcalcifications (MCs) detection in digital breast tomosynthesis (DBT), since there might be excessive false candidates in the detection stage. Considering that DBT volume has an aniso...
Algorithms Female Calcinosis Mammography Humans Neural Networks, Computer
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Development of a deep learning-based algorithm for the automatic detection and quantification of aortic valve calcium.

European journal of radiology Feb 6, 2021
PURPOSE: We aimed to develop a deep learning (DL)-based algorithm for automated quantification of aortic valve calcium (AVC) from non-enhanced electrocardiogram-gated cardiac CT scans and compare performance of DL-measured AVC volume and Agatston sco...
Severity of Illness Index Deep Learning Calcinosis Aortic Valve Stenosis Humans Algorithms Retrospective Studies Aortic Valve Calcium
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A deep learning model integrating mammography and clinical factors facilitates the malignancy prediction of BI-RADS 4 microcalcifications in breast cancer screening.

European radiology Jan 26, 2021
OBJECTIVES: To investigate the value of full-field digital mammography-based deep learning (DL) in predicting malignancy of Breast Imaging Reporting and Data System (BI-RADS) 4 microcalcifications.
Retrospective Studies Female Breast Neoplasms Deep Learning Early Detection of Cancer Calcinosis Mammography Humans Artificial Intelligence
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Network-based screen in iPSC-derived cells reveals therapeutic candidate for heart valve disease.

Science (New York, N.Y.) Dec 10, 2020
Mapping the gene-regulatory networks dysregulated in human disease would allow the design of network-correcting therapies that treat the core disease mechanism. However, small molecules are traditionally screened for their effects on one to several o...
Haploinsufficiency Mice, Inbred C57BL Aortic Valve Disease Calcinosis Humans Aortic Valve Stenosis Small Molecule Libraries Machine Learning Aortic Valve Induced Pluripotent Stem Cells Drug Evaluation, Preclinical Receptor, Notch1 RNA-Seq Algorithms Thiazoles Gene Regulatory Networks Animals Gene Expression Regulation Mice Drug Discovery Nitriles Disease Models, Animal
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Deep learning for automated exclusion of cardiac CT examinations negative for coronary artery calcium.

European journal of radiology Jun 3, 2020
PURPOSE: Coronary artery calcium (CAC) score has shown to be an accurate predictor of future cardiovascular events. Early detection by CAC scoring might reduce the number of deaths by cardiovascular disease (CVD). Automatically excluding scans which ...
Middle Aged Deep Learning Calcinosis Female Radiographic Image Interpretation, Computer-Assisted Risk Factors Coronary Artery Disease Aged Humans Coronary Vessels Male Tomography, X-Ray Computed
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A machine learning approach on multiscale texture analysis for breast microcalcification diagnosis.

BMC bioinformatics Mar 11, 2020
BACKGROUND: Screening programs use mammography as primary diagnostic tool for detecting breast cancer at an early stage. The diagnosis of some lesions, such as microcalcifications, is still difficult today for radiologists. In this paper, we proposed...
Humans Breast Machine Learning ROC Curve Algorithms Calcinosis Databases, Factual Mammography Female Area Under Curve Breast Neoplasms
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A Hybridized ELM for Automatic Micro Calcification Detection in Mammogram Images Based on Multi-Scale Features.

Journal of medical systems May 15, 2019
Detection of masses and micro calcifications are a stimulating task for radiologists in digital mammogram images. Radiologists using Computer Aided Detection (CAD) frameworks to find the breast lesion. Micro calcification may be the early sign of bre...
Mammography Radiographic Image Enhancement Female Diagnosis, Computer-Assisted Calcinosis Humans Machine Learning Algorithms
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Convolutional Neural Networks for the Segmentation of Microcalcification in Mammography Imaging.

Journal of healthcare engineering Apr 9, 2019
Cluster of microcalcifications can be an early sign of breast cancer. In this paper, we propose a novel approach based on convolutional neural networks for the detection and segmentation of microcalcification clusters. In this work, we used 283 mammo...
Mammography Female Diagnosis, Differential Humans Radiographic Image Enhancement Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Breast Neoplasms Algorithms Calcinosis
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