AIMC Topic: Female

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High-throughput quantitative histology in systemic sclerosis skin disease using computer vision.

Arthritis research & therapy Mar 14, 2020
BACKGROUND: Skin fibrosis is the clinical hallmark of systemic sclerosis (SSc), where collagen deposition and remodeling of the dermis occur over time. The most widely used outcome measure in SSc clinical trials is the modified Rodnan skin score (mRS...
Humans Neural Networks, Computer Algorithms Female Scleroderma, Systemic Eosine Yellowish-(YS) Methyl Green Scleroderma, Localized Cohort Studies Adult Principal Component Analysis Male Biopsy Middle Aged Skin Severity of Illness Index Deep Learning Azo Compounds
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Deep convolutional neural network-based detection of meniscus tears: comparison with radiologists and surgery as standard of reference.

Skeletal radiology Mar 13, 2020
OBJECTIVE: To clinically validate a fully automated deep convolutional neural network (DCNN) for detection of surgically proven meniscus tears.
Magnetic Resonance Imaging Radiologists Arthroscopy Reference Standards Tibial Meniscus Injuries Sensitivity and Specificity Male Middle Aged Clinical Competence Adolescent Humans Neural Networks, Computer Retrospective Studies Female Aged Adult
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Non-Standardized Patch-Based ECG Lead Together With Deep Learning Based Algorithm for Automatic Screening of Atrial Fibrillation.

IEEE journal of biomedical and health informatics Mar 13, 2020
This study was to assess the feasibility of using non-standardized single-lead electrocardiogram (ECG) monitoring to automatically detect atrial fibrillation (AF) with special emphasis on the combination of deep learning based algorithm and modified ...
Deep Learning Electrocardiography Equipment Design Signal Processing, Computer-Assisted Atrial Fibrillation Humans Aged, 80 and over Neural Networks, Computer Adult Algorithms Male Female Middle Aged Aged Diagnosis, Computer-Assisted
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Human respiration monitoring using infrared thermography and artificial intelligence.

Biomedical physics & engineering express Mar 13, 2020
The respiration rate (RR) is the most vital parameter used for the determination of human health. The most widely adopted techniques, used to monitor the RR are contact in nature and face many drawbacks. This paper reports the use of Infrared Thermog...
Humans Artificial Intelligence Normal Distribution Respiratory Rate Monitoring, Physiologic Adult Algorithms Respiration Models, Statistical Sensitivity and Specificity Female Equipment Design Signal-To-Noise Ratio Male Signal Processing, Computer-Assisted Temperature Infrared Rays Adolescent Body Temperature Reproducibility of Results Thermography Support Vector Machine Young Adult Stochastic Processes
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Artificial neural network-based models used for predicting 28- and 90-day mortality of patients with hepatitis B-associated acute-on-chronic liver failure.

BMC gastroenterology Mar 13, 2020
BACKGROUND: This study aimed to develop prognostic models for predicting 28- and 90-day mortality rates of hepatitis B virus (HBV)-associated acute-on-chronic liver failure (HBV-ACLF) through artificial neural network (ANN) systems.
Age Factors Female gamma-Glutamyltransferase Acute-On-Chronic Liver Failure Humans Risk Factors Bilirubin Hepatitis B e Antigens Neural Networks, Computer Adult Prothrombin Time Alkaline Phosphatase Prognosis Male Hepatic Encephalopathy Sodium Retrospective Studies Hepatitis B
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Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN).

IEEE journal of biomedical and health informatics Mar 12, 2020
The medical and machine learning communities are relying on the promise of artificial intelligence (AI) to transform medicine through enabling more accurate decisions and personalized treatment. However, progress is slow. Legal and ethical issues aro...
Humans Neural Networks, Computer Electronic Health Records Female Male Data Anonymization Information Dissemination
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Impact of machine-learning CT-derived fractional flow reserve for the diagnosis and management of coronary artery disease in the randomized CRESCENT trials.

European radiology Mar 12, 2020
OBJECTIVE: To determine the potential impact of on-site CT-derived fractional flow reserve (CT-FFR) on the diagnostic efficiency and effectiveness of coronary CT angiography (CCTA) in patients with obstructive coronary artery disease (CAD) on CCTA.
Tomography, X-Ray Computed Female Aged Male Middle Aged Humans Disease Management Hemodynamics Cardiac Catheterization Machine Learning Cohort Studies Retrospective Studies Coronary Angiography Computed Tomography Angiography Percutaneous Coronary Intervention Coronary Stenosis Coronary Artery Disease Fractional Flow Reserve, Myocardial
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A knowledge-driven feature learning and integration method for breast cancer diagnosis on multi-sequence MRI.

Magnetic resonance imaging Mar 12, 2020
BACKGROUND: The classification of benign versus malignant breast lesions on multi-sequence Magnetic Resonance Imaging (MRI) is a challenging task since breast lesions are heterogeneous and complex. Recently, deep learning methods have been used for b...
Deep Learning ROC Curve Image Processing, Computer-Assisted Magnetic Resonance Imaging Models, Statistical Image Interpretation, Computer-Assisted Humans Algorithms Female Breast Neoplasms Diagnosis, Computer-Assisted
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Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records.

The Lancet. Digital health Mar 12, 2020
BACKGROUND: Many mortality prediction models have been developed for patients in intensive care units (ICUs); most are based on data available at ICU admission. We investigated whether machine learning methods using analyses of time-series data impro...
Electronic Health Records Female Hospitalization Aged Male Algorithms Prognosis Retrospective Studies Critical Illness Intensive Care Units Area Under Curve Models, Biological Simplified Acute Physiology Score Middle Aged Risk Assessment Cohort Studies Hospital Mortality ROC Curve Humans Machine Learning Data Analysis
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Stroke Prediction with Machine Learning Methods among Older Chinese.

International journal of environmental research and public health Mar 12, 2020
Timely stroke diagnosis and intervention are necessary considering its high prevalence. Previous studies have mainly focused on stroke prediction with balanced data. Thus, this study aimed to develop machine learning models for predicting stroke with...
Aged Male China Humans Support Vector Machine Stroke Machine Learning Forecasting Prospective Studies Prognosis Female
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