AIMC Topic: ROC Curve

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Biological signatures and prediction of an immunosuppressive status-persistent critical illness-among orthopedic trauma patients using machine learning techniques.

Frontiers in immunology Oct 17, 2022
BACKGROUND: Persistent critical illness (PerCI) is an immunosuppressive status. The underlying pathophysiology driving PerCI remains incompletely understood. The objectives of the study were to identify the biological signature of PerCI development, ...
Risk Factors Organ Dysfunction Scores Machine Learning ROC Curve Critical Illness Humans
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DeepMPM: a mortality risk prediction model using longitudinal EHR data.

BMC bioinformatics Oct 14, 2022
BACKGROUND: Accurate precision approaches have far not been developed for modeling mortality risk in intensive care unit (ICU) patients. Conventional mortality risk prediction methods can hardly extract the information in longitudinal electronic medi...
Machine Learning Databases, Factual Electronic Health Records ROC Curve Humans
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A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning.

BMC bioinformatics Oct 14, 2022
BACKGROUND: Selecting and prioritizing candidate disease genes is necessary before conducting laboratory studies as identifying disease genes from a large number of candidate genes using laboratory methods, is a very costly and time-consuming task. T...
ROC Curve Area Under Curve Neural Networks, Computer Machine Learning Supervised Machine Learning
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Diagnostic performance of convolutional neural networks for dental sexual dimorphism.

Scientific reports Oct 14, 2022
Convolutional neural networks (CNN) led to important solutions in the field of Computer Vision. More recently, forensic sciences benefited from the resources of artificial intelligence, especially in procedures that normally require operator-dependen...
Neural Networks, Computer Artificial Intelligence Humans Area Under Curve Sex Characteristics Male ROC Curve Machine Learning Female
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Modelling flood susceptibility based on deep learning coupling with ensemble learning models.

Journal of environmental management Oct 11, 2022
Modelling flood susceptibility is an indirect way to reduce the loss from flood disaster. Now, flood susceptibility modelling based on data driven model is state-of-the-art method such as ensemble learning and deep learning. However, the effect of de...
Floods Forests Disasters Deep Learning ROC Curve
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Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder.

Scientific reports Oct 11, 2022
Discrimination of ovarian tumors is necessary for proper treatment. In this study, we developed a convolutional neural network model with a convolutional autoencoder (CNN-CAE) to classify ovarian tumors. A total of 1613 ultrasound images of ovaries w...
Humans ROC Curve Ovarian Neoplasms Neural Networks, Computer Female
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Development and validation of a pixel wise deep learning model to detect cataract on swept-source optical coherence tomography images.

Journal of optometry Oct 10, 2022
PURPOSE: The diagnosis of cataract is mostly clinical and there is a lack of objective and specific tool to detect and grade it automatically. The goal of this study was to develop and validate a deep learning model to detect and localize cataract on...
Tomography, Optical Coherence Cataract Deep Learning ROC Curve Lens, Crystalline Humans
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Detection of Proximal Caries Lesions on Bitewing Radiographs Using Deep Learning Method.

Caries research Oct 10, 2022
This study aimed to evaluate the validity of a deep learning-based convolutional neural network (CNN) for detecting proximal caries lesions on bitewing radiographs. A total of 978 bitewing radiographs, 10,899 proximal surfaces, were evaluated by two ...
Dental Caries Susceptibility Radiography, Bitewing Sensitivity and Specificity ROC Curve Deep Learning Humans Dental Caries
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Improving breast cancer diagnostics with deep learning for MRI.

Science translational medicine Sep 28, 2022
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a high sensitivity in detecting breast cancer but often leads to unnecessary biopsies and patient workup. We used a deep learning (DL) system to improve the overall accuracy of breast...
Magnetic Resonance Imaging Humans Deep Learning Female Retrospective Studies ROC Curve Breast Neoplasms
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Deep Learning-Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine Sep 22, 2022
To improve diagnostic accuracy, myocardial perfusion imaging (MPI) SPECT studies can use CT-based attenuation correction (AC). However, CT-based AC is not available for most SPECT systems in clinical use, increases radiation exposure, and is impacted...
Myocardial Perfusion Imaging Tomography, Emission-Computed, Single-Photon Sensitivity and Specificity Deep Learning Humans ROC Curve Coronary Artery Disease
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