AIMC Topic: Sensitivity and Specificity

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Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI.

European radiology Apr 23, 2019
OBJECTIVES: To develop and validate a proof-of-concept convolutional neural network (CNN)-based deep learning system (DLS) that classifies common hepatic lesions on multi-phasic MRI.
ROC Curve Liver Neoplasms Carcinoma, Hepatocellular United States Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Bile Duct Neoplasms Cholangiocarcinoma Bile Ducts, Intrahepatic Adult Sensitivity and Specificity Male Middle Aged Deep Learning Humans Neural Networks, Computer Female Reproducibility of Results Aged
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Accuracy of American College of Surgeons National Surgical Quality Improvement Program Universal Surgical Risk Calculator in Predicting Complications Following Robot-Assisted Radical Cystectomy at a National Comprehensive Cancer Center.

Journal of endourology Apr 22, 2019
There is paucity of literature about the validation of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical risk calculator for prediction of outcomes after robot-assisted radical cystectomy (RARC). We ...
Decision Support Techniques Retrospective Studies Female Aged Aged, 80 and over United States Sensitivity and Specificity Humans Robotics Male Area Under Curve Risk Assessment Quality Improvement Postoperative Complications Cystectomy ROC Curve
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Simulating Dual-Energy X-Ray Absorptiometry in CT Using Deep-Learning Segmentation Cascade.

Journal of the American College of Radiology : JACR Apr 12, 2019
PURPOSE: Osteoporosis is an underdiagnosed condition despite effective screening modalities. Dual-energy x-ray absorptiometry (DEXA) screening, although recommended in clinical guidelines, remains markedly underutilized. In contrast to DEXA, CT utili...
Humans Deep Learning Computer Simulation Aged Lumbar Vertebrae Bone Density Aged, 80 and over Absorptiometry, Photon Osteoporosis Sensitivity and Specificity Tomography, X-Ray Computed Male Female Middle Aged
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Lungs nodule detection framework from computed tomography images using support vector machine.

Microscopy research and technique Apr 11, 2019
The emergence of cloud infrastructure has the potential to provide significant benefits in a variety of areas in the medical imaging field. The driving force behind the extensive use of cloud infrastructure for medical image processing is the exponen...
Lung Image Processing, Computer-Assisted Lung Neoplasms Support Vector Machine False Positive Reactions Humans Tomography, X-Ray Computed Sensitivity and Specificity
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Predicting daily outcomes in acetaminophen-induced acute liver failure patients with machine learning techniques.

Computer methods and programs in biomedicine Apr 11, 2019
BACKGROUND/OBJECTIVE: Assessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF) patients during the first week of hospitalization often presents significant challenges. Current models such as the King's College Criteria (KCC) and t...
Female Adult Sensitivity and Specificity Male Middle Aged Humans Machine Learning Databases, Factual Prognosis Retrospective Studies Severity of Illness Index ROC Curve Treatment Outcome Bayes Theorem Predictive Value of Tests Registries Area Under Curve Linear Models Acetaminophen Liver Failure, Acute
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Application of Artificial Neural Networks to Identify Alzheimer's Disease Using Cerebral Perfusion SPECT Data.

International journal of environmental research and public health Apr 11, 2019
The aim of this study was to demonstrate the usefulness of artificial neural networks in Alzheimer disease diagnosis (AD) using data of brain single photon emission computed tomography (SPECT). The results were compared with discriminant analysis. Th...
Male Middle Aged Case-Control Studies ROC Curve Discriminant Analysis Neural Networks, Computer Alzheimer Disease Female Tomography, Emission-Computed, Single-Photon Aged Humans Aged, 80 and over Sensitivity and Specificity
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Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms.

Computer methods and programs in biomedicine Apr 10, 2019
OBJECTIVE: A colon microarray data is a repository of thousands of gene expressions with different strengths for each cancer cell. It is necessary to detect which genes are responsible for cancer growth. This study presents an exhaustive comparative ...
Regression Analysis Colon Humans Colonic Neoplasms Decision Trees Neural Networks, Computer Gene Expression Profiling Risk Machine Learning Normal Distribution Area Under Curve Sensitivity and Specificity Logistic Models Bayes Theorem Oncogenes Support Vector Machine Discriminant Analysis Tissue Array Analysis Models, Statistical
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Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task.

European journal of cancer (Oxford, England : 1990) Apr 10, 2019
BACKGROUND: Recent studies have successfully demonstrated the use of deep-learning algorithms for dermatologist-level classification of suspicious lesions by the use of excessive proprietary image databases and limited numbers of dermatologists. For ...
Hospitals, University Germany Nevus Humans Melanoma Skin Neoplasms Dermoscopy Sensitivity and Specificity Deep Learning Dermatologists
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Plaque components segmentation in carotid artery on simultaneous non-contrast angiography and intraplaque hemorrhage imaging using machine learning.

Magnetic resonance imaging Apr 5, 2019
PURPOSE: This study sought to determine the feasibility of using Simultaneous Non-contrast Angiography and intraPlaque Hemorrhage (SNAP) to detect the lipid-rich/necrotic core (LRNC), and develop a machine learning based algorithm to segment plaque c...
Humans Machine Learning Algorithms Female Reproducibility of Results Calcinosis Lipids Cerebral Hemorrhage Bayes Theorem Carotid Arteries Aged Sensitivity and Specificity Male Middle Aged Contrast Media Plaque, Amyloid Carotid Artery, Common Plaque, Atherosclerotic Angiography Necrosis Carotid Stenosis
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Application of MR morphologic, diffusion tensor, and perfusion imaging in the classification of brain tumors using machine learning scheme.

Neuroradiology Apr 4, 2019
PURPOSE: While MRI is the modality of choice for the assessment of patients with brain tumors, differentiation between various tumors based on their imaging characteristics might be challenging due to overlapping imaging features. The purpose of this...
Diagnosis, Differential Glioblastoma Image Interpretation, Computer-Assisted Aged Meningioma Aged, 80 and over Adult Sensitivity and Specificity Humans Male Brain Neoplasms Machine Learning Middle Aged Prospective Studies Adolescent Female Lymphoma Magnetic Resonance Imaging
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