AIMC Topic: ROC Curve

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Predictive modeling in pediatric traumatic brain injury using machine learning.

BMC medical research methodology Mar 17, 2015
BACKGROUND: Pediatric traumatic brain injury (TBI) constitutes a significant burden and diagnostic challenge in the emergency department (ED). While large North American research networks have derived clinical prediction rules for the head injured ch...
Case-Control Studies Child, Preschool Child ROC Curve Logistic Models Retrospective Studies Tomography, X-Ray Computed Female Male Multivariate Analysis Injury Severity Score Vomiting Unconsciousness Models, Theoretical Brain Injuries Population Surveillance Accidents, Traffic Skull Fractures Humans Machine Learning Algorithms Databases, Factual
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Bridging a translational gap: using machine learning to improve the prediction of PTSD.

BMC psychiatry Mar 16, 2015
BACKGROUND: Predicting Posttraumatic Stress Disorder (PTSD) is a pre-requisite for targeted prevention. Current research has identified group-level risk-indicators, many of which (e.g., head trauma, receiving opiates) concern but a subset of survivor...
Stress Disorders, Post-Traumatic ROC Curve Translational Research, Biomedical Early Diagnosis Adaptation, Psychological Wounds and Injuries Risk Factors Adult Male Middle Aged Risk Assessment Artificial Intelligence Algorithms Prognosis Female Humans
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Automatic detection of atrial fibrillation using stationary wavelet transform and support vector machine.

Computers in biology and medicine Mar 14, 2015
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Automatic detection of AF could substantially help in early diagnosis, management and co...
Humans ROC Curve Algorithms Atrial Fibrillation Electrocardiography Reproducibility of Results Wavelet Analysis Support Vector Machine Sensitivity and Specificity Fourier Analysis Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted Arrhythmias, Cardiac
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Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

Annals of surgical oncology Mar 10, 2015
BACKGROUND: The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, convent...
Bayes Theorem Carcinoma, Ovarian Epithelial Cytoreduction Surgical Procedures Proportional Hazards Models Neoplasms, Glandular and Epithelial Support Vector Machine Decision Trees Ovarian Neoplasms Predictive Value of Tests Area Under Curve Humans Neural Networks, Computer Algorithms Prognosis Female Survival Rate ROC Curve
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Efficient prediction of progesterone receptor interactome using a support vector machine model.

International journal of molecular sciences Mar 3, 2015
Protein-protein interaction (PPI) is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, p...
Area Under Curve Receptors, Androgen Receptors, Estrogen Humans Receptors, Progesterone ROC Curve Protein Interaction Domains and Motifs Proteome Support Vector Machine Cluster Analysis
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An efficient machine learning approach for diagnosis of paraquat-poisoned patients.

Computers in biology and medicine Feb 12, 2015
Numerous people die of paraquat (PQ) poisoning because they were not diagnosed and treated promptly at an early stage. Till now, determination of PQ levels in blood or urine is still the only way to confirm the PQ poisoning. In order to develop a new...
Diagnosis, Computer-Assisted Adolescent ROC Curve Paraquat Poisoning Young Adult Adult Humans Male Machine Learning Middle Aged Female
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Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine.

Biomedical engineering online Feb 12, 2015
BACKGROUND: Lung cancer is a leading cause of death worldwide; it refers to the uncontrolled growth of abnormal cells in the lung. A computed tomography (CT) scan of the thorax is the most sensitive method for detecting cancerous lung nodules. A lung...
Area Under Curve Wavelet Analysis Humans ROC Curve Radiographic Image Interpretation, Computer-Assisted Imaging, Three-Dimensional Incidental Findings Algorithms Referral and Consultation Lung Neoplasms Tomography, X-Ray Computed Automation Sensitivity and Specificity Support Vector Machine Pattern Recognition, Automated Solitary Pulmonary Nodule
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Analysis of the impact of adherent perirenal fat on peri-operative outcomes of robotic partial nephrectomy.

World journal of urology Feb 11, 2015
INTRODUCTION: Adherent perirenal fat (APF) can be defined as inflammatory fat sticking to renal parenchyma, whose dissection is difficult and makes it troublesome to expose the tumour. Our objective was to evaluate the impact of APF on the technical ...
Middle Aged Carcinoma, Renal Cell Postoperative Complications Nephrectomy Incidence ROC Curve Kidney Humans Predictive Value of Tests Retrospective Studies Robotics Female Body Mass Index Laparoscopy Risk Factors Follow-Up Studies France Male Operative Time Kidney Neoplasms Adipose Tissue
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Automated confidence ranked classification of randomized controlled trial articles: an aid to evidence-based medicine.

Journal of the American Medical Informatics Association : JAMIA Feb 5, 2015
OBJECTIVE: For many literature review tasks, including systematic review (SR) and other aspects of evidence-based medicine, it is important to know whether an article describes a randomized controlled trial (RCT). Current manual annotation is not com...
Humans Artificial Intelligence ROC Curve Support Vector Machine Evidence-Based Medicine Randomized Controlled Trials as Topic Review Literature as Topic Information Storage and Retrieval MEDLINE
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Phase information of time-frequency transforms as a key feature for classification of atrial fibrillation episodes.

Physiological measurement Feb 5, 2015
Patients suffering from atrial fibrillation can be classified into different subtypes, according to the temporal pattern of the arrhythmia and its recurrence. Nowadays, clinicians cannot differentiate a priori between the different subtypes, and pati...
Hypertension Adult Electrocardiography Sensitivity and Specificity Support Vector Machine Tertiary Care Centers Middle Aged Principal Component Analysis Humans Atrial Fibrillation Cohort Studies Area Under Curve Aged Fourier Analysis ROC Curve Aged, 80 and over Cardiovascular Agents
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