AIMC Topic: Predictive Value of Tests

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Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study.

JACC. Cardiovascular imaging Mar 14, 2018
OBJECTIVES: The study evaluated the automatic prediction of obstructive disease from myocardial perfusion imaging (MPI) by deep learning as compared with total perfusion deficit (TPD).
Humans Deep Learning Predictive Value of Tests Registries Radiopharmaceuticals Image Interpretation, Computer-Assisted Female Aged Aged, 80 and over Male Middle Aged Technetium Tc 99m Sestamibi Organotechnetium Compounds Organophosphorus Compounds Tomography, Emission-Computed, Single-Photon Coronary Circulation Myocardial Perfusion Imaging Coronary Stenosis
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Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning-An Artificial Intelligence Concept.

Journal of vascular and interventional radiology : JVIR Mar 14, 2018
PURPOSE: To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of transarterial chemoembolization by applying machine learning (ML) techniques.
Chemoembolization, Therapeutic Ethiodized Oil Contrast Media Female Magnetic Resonance Imaging Predictive Value of Tests Aged Neoplasm Staging Adult Middle Aged Doxorubicin Sensitivity and Specificity Antineoplastic Agents Male Liver Neoplasms Humans Carcinoma, Hepatocellular Machine Learning Treatment Outcome Retrospective Studies
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A new scheme for strain typing of methicillin-resistant Staphylococcus aureus on the basis of matrix-assisted laser desorption ionization time-of-flight mass spectrometry by using machine learning approach.

PloS one Mar 13, 2018
Methicillin-resistant Staphylococcus aureus (MRSA), one of the most important clinical pathogens, conducts an increasing number of morbidity and mortality in the world. Rapid and accurate strain typing of bacteria would facilitate epidemiological inv...
Staphylococcal Infections Humans Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Machine Learning Cost-Benefit Analysis Methicillin-Resistant Staphylococcus aureus Multilocus Sequence Typing Cluster Analysis Bacterial Typing Techniques Predictive Value of Tests
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Multichannel lung sound analysis for asthma detection.

Computer methods and programs in biomedicine Mar 9, 2018
BACKGROUND AND OBJECTIVE: Lung sound signals convey valuable information of the lung status. Auscultation is an effective technique to appreciate the condition of the respiratory system using lung sound signals. The prior works on asthma detection fr...
Vital Capacity Normal Distribution Auscultation Respiratory Sounds Support Vector Machine Models, Statistical Predictive Value of Tests Forced Expiratory Volume Signal Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms Female Young Adult Adult Asthma Male Middle Aged Lung
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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 Magnetic Resonance Imaging Predictive Value of Tests Osteoarthritis, Knee Cartilage, Articular Menisci, Tibial Male Middle Aged Disease Progression Time Factors Follow-Up Studies
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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...
Urine False Positive Reactions Emergency Service, Hospital Urinary Tract Infections Models, Biological Humans Early Diagnosis Machine Learning False Negative Reactions Retrospective Studies Male Female Middle Aged Sensitivity and Specificity ROC Curve Predictive Value of Tests Area Under Curve
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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).
Adult Male Middle Aged ROC Curve Age Factors Decision Making Predictive Value of Tests Models, Biological Computed Tomography Angiography Cerebral Angiography Female Risk Factors Aged Aged, 80 and over Young Adult Humans Neural Networks, Computer Aneurysm, Ruptured Intracranial Aneurysm Anterior Cerebral Artery
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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).
Humans Supervised Machine Learning Databases, Factual Florida Intensive Care Units Simplified Acute Physiology Score Bacteremia Logistic Models Predictive Value of Tests Central Venous Catheters Catheter-Related Infections Female Male Middle Aged Risk Assessment Hospital Mortality
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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...
Equipment Design Machine Learning Signal Processing, Computer-Assisted Transducers Diagnosis, Computer-Assisted Humans Activities of Daily Living Time Factors Electromagnetic Phenomena Neural Networks, Computer Parkinson Disease Motor Activity Predictive Value of Tests
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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...
ROC Curve Recovery of Function Predictive Value of Tests Hearing Loss, Sensorineural Hearing Loss, Sudden Female Adult Male Middle Aged China Humans Machine Learning Prognosis Retrospective Studies
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