AIMC Topic:
ROC Curve

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Machine learning based on multi-parametric magnetic resonance imaging to differentiate glioblastoma multiforme from primary cerebral nervous system lymphoma.

European journal of radiology Sep 14, 2018
PURPOSE: To evaluate the performance of a machine learning method based on texture features in multi-parametric magnetic resonance imaging (MRI) to differentiate a glioblastoma multiforme (GBM) from a primary cerebral nervous system lymphoma (PCNSL).
Machine Learning Brain Retrospective Studies Female Humans Middle Aged ROC Curve Logistic Models Lymphoma Diagnosis, Differential Magnetic Resonance Imaging Aged Glioblastoma Adult Image Enhancement Brain Neoplasms Male
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Performance and clinical impact of machine learning based lung nodule detection using vessel suppression in melanoma patients.

Clinical imaging Sep 11, 2018
PURPOSE: To evaluate performance and the clinical impact of a novel machine learning based vessel-suppressing computer-aided detection (CAD) software in chest computed tomography (CT) of patients with malignant melanoma.
Neoplasm Metastasis Multidetector Computed Tomography Aged Aged, 80 and over Adult Male ROC Curve Retrospective Studies Lung Neoplasms Middle Aged Female Diagnosis, Computer-Assisted Melanoma, Cutaneous Malignant Melanoma Humans Skin Neoplasms Machine Learning
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Overall survival prediction in glioblastoma multiforme patients from volumetric, shape and texture features using machine learning.

Surgical oncology Sep 10, 2018
Glioblastoma multiforme (GBM) are aggressive brain tumors, which lead to poor overall survival (OS) of patients. OS prediction of GBM patients provides useful information for surgical and treatment planning. Radiomics research attempts at predicting ...
Humans Magnetic Resonance Imaging Survival Rate Machine Learning Models, Statistical Brain Neoplasms Glioblastoma Disease Progression Algorithms ROC Curve Prognosis
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Using predicate and provenance information from a knowledge graph for drug efficacy screening.

Journal of biomedical semantics Sep 6, 2018
BACKGROUND: Biomedical knowledge graphs have become important tools to computationally analyse the comprehensive body of biomedical knowledge. They represent knowledge as subject-predicate-object triples, in which the predicate indicates the relation...
Biological Ontologies False Negative Reactions Computer Graphics ROC Curve Drug Evaluation, Preclinical
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Machine Learning and Primary Total Knee Arthroplasty: Patient Forecasting for a Patient-Specific Payment Model.

The Journal of arthroplasty Sep 5, 2018
BACKGROUND: Value-based and patient-specific care represent 2 critical areas of focus that have yet to be fully reconciled by today's bundled care model. Using a predictive naïve Bayesian model, the objectives of this study were (1) to develop a mach...
Length of Stay ROC Curve Inpatients Bayes Theorem Machine Learning Patient Care Bundles Costs and Cost Analysis Humans Algorithms Health Expenditures Patient-Specific Modeling Databases, Factual Models, Economic Comorbidity Arthroplasty, Replacement, Knee
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Parkinson's Disease Diagnosis via Joint Learning From Multiple Modalities and Relations.

IEEE journal of biomedical and health informatics Sep 3, 2018
Parkinson's disease (PD) is a neurodegenerative progressive disease that mainly affects the motor systems of patients. To slow this disease deterioration, early and accurate diagnosis of PD is an effective way, which alleviates mental and physical su...
Algorithms Brain Female Aged Humans Machine Learning Multimodal Imaging Image Interpretation, Computer-Assisted Diffusion Tensor Imaging Male Middle Aged ROC Curve Parkinson Disease
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Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis.

European radiology Sep 3, 2018
OBJECTIVE: To assess significant liver fibrosis by multiparametric ultrasomics data using machine learning.
Humans Neural Networks, Computer Ultrasonography Female ROC Curve Adult Machine Learning Area Under Curve Logistic Models Male Algorithms Support Vector Machine Hepatitis B, Chronic Liver Cirrhosis Middle Aged Decision Support Techniques Decision Trees Prospective Studies
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Performance of the deep convolutional neural network based magnetic resonance image scoring algorithm for differentiating between tuberculous and pyogenic spondylitis.

Scientific reports Sep 3, 2018
The purpose of this study was to evaluate the performance of the deep convolutional neural network (DCNN) in differentiating between tuberculous and pyogenic spondylitis on magnetic resonance (MR) imaging, compared to the performance of three skilled...
Aged Adult Male Middle Aged Neural Networks, Computer Algorithms Retrospective Studies Female Spine Supervised Machine Learning Image Interpretation, Computer-Assisted Spondylitis Tuberculosis, Osteoarticular ROC Curve Humans Magnetic Resonance Imaging Diagnosis, Differential Area Under Curve
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A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia.

Journal of neuroscience methods Sep 2, 2018
BACKGROUND: Technological advances are enabling us to collect multimodal datasets at an increasing depth and resolution while with decreasing labors. Understanding complex interactions among multimodal datasets, however, is challenging.
Neuroimaging Multivariate Analysis Machine Learning Algorithms Computer Simulation Female Adult Male ROC Curve Schizophrenia Humans
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Support Vector Machines and logistic regression to predict temporal artery biopsy outcomes.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie Aug 31, 2018
OBJECTIVE: Support vector machines (SVM) is a newer statistical method that has been reported to be advantageous to traditional logistic regression for clinical classification. We determine if SVM can better predict the results of temporal artery bio...
Predictive Value of Tests Humans ROC Curve Biopsy Logistic Models Giant Cell Arteritis Support Vector Machine Temporal Arteries
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