AIMC Topic:
ROC Curve

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Identification of Latent Oncogenes with a Network Embedding Method and Random Forest.

BioMed research international Sep 23, 2020
Oncogene is a special type of genes, which can promote the tumor initiation. Good study on oncogenes is helpful for understanding the cause of cancers. Experimental techniques in early time are quite popular in detecting oncogenes. However, their def...
Humans Oncogenes Computational Biology Neoplasms Databases, Genetic Machine Learning ROC Curve Cell Transformation, Neoplastic Algorithms Protein Interaction Maps
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A deep learning solution to recommend laboratory reduction strategies in ICU.

International journal of medical informatics Sep 22, 2020
OBJECTIVE: To build a machine-learning model that predicts laboratory test results and provides a promising lab test reduction strategy, using spatial-temporal correlations.
Humans Laboratories Machine Learning Intensive Care Units Deep Learning ROC Curve
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Application of machine learning to the prediction of postoperative sepsis after appendectomy.

Surgery Sep 18, 2020
BACKGROUND: We applied various machine learning algorithms to a large national dataset to model the risk of postoperative sepsis after appendectomy to evaluate utility of such methods and identify factors associated with postoperative sepsis in these...
Middle Aged Postoperative Complications Sepsis Public Health Surveillance Factor Analysis, Statistical ROC Curve Models, Theoretical Female Adult Male Humans Machine Learning Prognosis Area Under Curve Disease Susceptibility Appendectomy
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Automated Quality Assessment and Image Selection of Ultra-Widefield Fluorescein Angiography Images through Deep Learning.

Translational vision science & technology Sep 17, 2020
PURPOSE: Numerous angiographic images with high variability in quality are obtained during each ultra-widefield fluorescein angiography (UWFA) acquisition session. This study evaluated the feasibility of an automated system for image quality classifi...
Deep Learning ROC Curve Fluorescein Angiography
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Deep learning for automated glaucomatous optic neuropathy detection from ultra-widefield fundus images.

The British journal of ophthalmology Sep 16, 2020
BACKGROUND/AIMS: To develop a deep learning system for automated glaucomatous optic neuropathy (GON) detection using ultra-widefield fundus (UWF) images.
Humans Glaucoma Deep Learning Optic Nerve Diseases ROC Curve Fundus Oculi Optic Disk
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Evaluation of the Classification Accuracy of the Kidney Biopsy Direct Immunofluorescence through Convolutional Neural Networks.

Clinical journal of the American Society of Nephrology : CJASN Sep 16, 2020
BACKGROUND AND OBJECTIVES: Immunohistopathology is an essential technique in the diagnostic workflow of a kidney biopsy. Deep learning is an effective tool in the elaboration of medical imaging. We wanted to evaluate the role of a convolutional neura...
Immunoglobulin lambda-Chains Fluorescent Antibody Technique, Direct Complement C1q Immunoglobulin kappa-Chains Middle Aged Kidney Neural Networks, Computer ROC Curve Kidney Diseases Female Image Processing, Computer-Assisted Area Under Curve Immunoglobulins Aged Humans Biopsy Complement C3 Adult Fibrinogen Male
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Evaluation of a multiview architecture for automatic vertebral labeling of palliative radiotherapy simulation CT images.

Medical physics Sep 15, 2020
PURPOSE: The purpose of this work was to evaluate the performance of X-Net, a multiview deep learning architecture, to automatically label vertebral levels (S2-C1) in palliative radiotherapy simulation CT scans.
Lumbar Vertebrae Computer Simulation Tomography, X-Ray Computed ROC Curve Humans Neural Networks, Computer
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Receiver operating characteristic curves and confidence bands for support vector machines.

Biometrics Sep 12, 2020
Many problems that appear in biomedical decision-making, such as diagnosing disease and predicting response to treatment, can be expressed as binary classification problems. The support vector machine (SVM) is a popular classification technique that ...
Support Vector Machine Female Humans Probability Breast Neoplasms Computer Simulation ROC Curve
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Temporal Lobe Epilepsy Surgical Outcomes Can Be Inferred Based on Structural Connectome Hubs: A Machine Learning Study.

Annals of neurology Sep 10, 2020
OBJECTIVE: Medial temporal lobe epilepsy (TLE) is the most common form of medication-resistant focal epilepsy in adults. Despite removal of medial temporal structures, more than one-third of patients continue to have disabling seizures postoperativel...
Treatment Outcome Humans Magnetic Resonance Imaging Gray Matter Neurosurgical Procedures Adult Nerve Net Connectome Middle Aged Male Epilepsy, Temporal Lobe Diffusion Tensor Imaging ROC Curve Drug Resistant Epilepsy Machine Learning Image Processing, Computer-Assisted Parahippocampal Gyrus Female
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Automated detection of cribriform growth patterns in prostate histology images.

Scientific reports Sep 10, 2020
Cribriform growth patterns in prostate carcinoma are associated with poor prognosis. We aimed to introduce a deep learning method to detect such patterns automatically. To do so, convolutional neural network was trained to detect cribriform growth pa...
Humans Neural Networks, Computer Adenocarcinoma Prostatic Neoplasms Neoplasm Grading Observer Variation Male ROC Curve Image Processing, Computer-Assisted Biopsy, Needle
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