AIMC Topic:
Predictive Value of Tests

Clear Filters Showing 1561 to 1570 of 2135 articles

Knee menisci segmentation using convolutional neural networks: data from the Osteoarthritis Initiative.

Osteoarthritis and cartilage Mar 9, 2018
OBJECTIVE: To present a novel method for automated segmentation of knee menisci from MRIs. To evaluate quantitative meniscal biomarkers for osteoarthritis (OA) estimated thereof.
Humans Neural Networks, Computer Female Male Middle Aged Magnetic Resonance Imaging Disease Progression Predictive Value of Tests Time Factors Osteoarthritis, Knee Follow-Up Studies Cartilage, Articular Menisci, Tibial
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Predicting urinary tract infections in the emergency department with machine learning.

PloS one Mar 7, 2018
BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) diagnosis with reported high diagnostic error rates. Because a urine culture, part of the gold standard for diagnosis of UTI, is usually not available for 24-48 hours aft...
Area Under Curve False Negative Reactions Sensitivity and Specificity Emergency Service, Hospital Humans Male Urine Urinary Tract Infections Machine Learning Middle Aged False Positive Reactions Models, Biological Retrospective Studies Early Diagnosis Female ROC Curve Predictive Value of Tests
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Prediction of rupture risk in anterior communicating artery aneurysms with a feed-forward artificial neural network.

European radiology Feb 23, 2018
OBJECTIVES: Anterior communicating artery (ACOM) aneurysms are the most common intracranial aneurysms, and predicting their rupture risk is challenging. We aimed to predict this risk using a two-layer feed-forward artificial neural network (ANN).
Cerebral Angiography Neural Networks, Computer Aneurysm, Ruptured Female Intracranial Aneurysm Risk Factors Anterior Cerebral Artery Aged Aged, 80 and over Humans Age Factors Decision Making Young Adult Predictive Value of Tests Adult Models, Biological Male Computed Tomography Angiography Middle Aged ROC Curve
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Predicting central line-associated bloodstream infections and mortality using supervised machine learning.

Journal of critical care Feb 21, 2018
PURPOSE: The purpose of this study was to compare machine learning techniques for predicting central line-associated bloodstream infection (CLABSI).
Hospital Mortality Bacteremia Logistic Models Predictive Value of Tests Central Venous Catheters Intensive Care Units Female Humans Male Catheter-Related Infections Databases, Factual Middle Aged Supervised Machine Learning Risk Assessment Florida Simplified Acute Physiology Score
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Using echo state networks for classification: A case study in Parkinson's disease diagnosis.

Artificial intelligence in medicine Feb 21, 2018
Despite having notable advantages over established machine learning methods for time series analysis, reservoir computing methods, such as echo state networks (ESNs), have yet to be widely used for practical data mining applications. In this paper, w...
Humans Neural Networks, Computer Motor Activity Machine Learning Diagnosis, Computer-Assisted Transducers Time Factors Parkinson Disease Predictive Value of Tests Equipment Design Signal Processing, Computer-Assisted Activities of Daily Living Electromagnetic Phenomena
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Predicting the hearing outcome in sudden sensorineural hearing loss via machine learning models.

Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery Feb 20, 2018
OBJECTIVE: Sudden sensorineural hearing loss (SSHL) is a multifactorial disorder with high heterogeneity, thus the outcomes vary widely. This study aimed to develop predictive models based on four machine learning methods for SSHL, identifying the be...
Hearing Loss, Sensorineural Hearing Loss, Sudden Middle Aged China ROC Curve Recovery of Function Humans Predictive Value of Tests Machine Learning Prognosis Retrospective Studies Female Adult Male
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Machine Learning Algorithms Utilizing Quantitative CT Features May Predict Eventual Onset of Bronchiolitis Obliterans Syndrome After Lung Transplantation.

Academic radiology Feb 19, 2018
RATIONALE AND OBJECTIVES: Long-term survival after lung transplantation (LTx) is limited by bronchiolitis obliterans syndrome (BOS), defined as a sustained decline in forced expiratory volume in the first second (FEV) not explained by other causes. W...
Lung Transplantation Bronchiolitis Obliterans Tomography, X-Ray Computed Female Humans Aged Machine Learning Adult Retrospective Studies Male Middle Aged Lung Predictive Value of Tests Tidal Volume Forced Expiratory Volume
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Sustained sensorimotor control as intermittent decisions about prediction errors: computational framework and application to ground vehicle steering.

Biological cybernetics Feb 16, 2018
A conceptual and computational framework is proposed for modelling of human sensorimotor control and is exemplified for the sensorimotor task of steering a car. The framework emphasises control intermittency and extends on existing models by suggesti...
Motor Activity Feedback, Sensory Computer Simulation Decision Making Predictive Value of Tests Automobile Driving Psychomotor Performance Humans Neural Networks, Computer
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An ontology-driven clinical decision support system (IDDAP) for infectious disease diagnosis and antibiotic prescription.

Artificial intelligence in medicine Feb 9, 2018
BACKGROUND: The available antibiotic decision-making systems were developed from a physician's perspective. However, because infectious diseases are common, many patients desire access to knowledge via a search engine. Although the use of antibiotics...
Drug Prescriptions Drug Therapy, Computer-Assisted ROC Curve Decision Support Systems, Clinical Bacterial Infections Predictive Value of Tests Biological Ontologies Humans Machine Learning Decision Support Techniques Anti-Bacterial Agents Clinical Decision-Making Reproducibility of Results Diagnosis, Computer-Assisted User-Computer Interface
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Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm.

The Journal of investigative dermatology Feb 8, 2018
We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-basal cell carcinoma, squamous cell carcinoma, intraepithelial carcinoma, actinic keratosis, seborrheic keratosis, malignant melanoma, melanocytic nevu...
Humans Software Female Male Middle Aged Deep Learning ROC Curve Image Processing, Computer-Assisted Skin Neoplasms Aged Aged, 80 and over Young Adult Adult Granuloma, Pyogenic Keratosis, Actinic Datasets as Topic Lentigo False Positive Reactions Diagnosis, Differential Photography Predictive Value of Tests Keratosis, Seborrheic Area Under Curve Warts Biopsy Skin
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