AIMC Topic: Predictive Value of Tests

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Detection of early infarction signs with machine learning-based diagnosis by means of the Alberta Stroke Program Early CT score (ASPECTS) in the clinical routine.

Neuroradiology Jul 31, 2018
PURPOSE: New software solutions emerged to support radiologists in image interpretation in acute ischemic stroke. This study aimed to validate the performance of computer-aided assessment of the Alberta Stroke Program Early CT score (ASPECTS) for det...
Brain Ischemia Observer Variation Alberta Aged Aged, 80 and over Adult Sensitivity and Specificity Male Middle Aged Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Stroke Infarction, Middle Cerebral Artery Humans Machine Learning Software Tomography, X-Ray Computed Female
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RETRACTED: Diagnosis labeling with disease-specific characteristics mining.

Artificial intelligence in medicine Jul 31, 2018
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the authors; serious errors had been introd...
Support Vector Machine Cluster Analysis Predictive Value of Tests Data Mining Pattern Recognition, Automated Humans Databases, Factual Intensive Care Units Electronic Health Records Diagnosis, Computer-Assisted
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Diagnostic performance of machine-learning-based computed fractional flow reserve (FFR) derived from coronary computed tomography angiography for the assessment of myocardial ischemia verified by invasive FFR.

The international journal of cardiovascular imaging Jul 30, 2018
To explore the diagnostic performance of a machine-learning-based (ML-based) computed fractional flow reserve (cFFR) derived from coronary computed tomography angiography (CCTA) in identifying ischemia-causing lesions verified by invasive FFR in cath...
Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Humans Machine Learning Radiographic Image Interpretation, Computer-Assisted Coronary Vessels Multidetector Computed Tomography Computed Tomography Angiography Coronary Stenosis Male Middle Aged Severity of Illness Index Predictive Value of Tests Coronary Angiography Fractional Flow Reserve, Myocardial Cardiac Catheters
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Estimating risk of severe neonatal morbidity in preterm births under 32 weeks of gestation.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians Jul 18, 2018
A large recent study analyzed the relationship between multiple factors and neonatal outcome and in preterm births. Study variables included the reason for admission, indication for delivery, optimal steroid use, gestational age, and other potential...
Risk Factors Adult Male Risk Assessment Infant Humans Prognosis Pregnancy Machine Learning Female Prospective Studies Infant, Newborn Gestational Age Premature Birth Stillbirth Severity of Illness Index Infant, Premature, Diseases Predictive Value of Tests Diagnostic Techniques, Obstetrical and Gynecological Morbidity Infant, Small for Gestational Age Probability Infant Mortality
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A neural network algorithm for detection of GI angiectasia during small-bowel capsule endoscopy.

Gastrointestinal endoscopy Jul 11, 2018
BACKGROUND AND AIMS: GI angiectasia (GIA) is the most common small-bowel (SB) vascular lesion, with an inherent risk of bleeding. SB capsule endoscopy (SB-CE) is the currently accepted diagnostic procedure. The aim of this study was to develop a comp...
Middle Aged Diagnosis, Computer-Assisted Predictive Value of Tests Capsule Endoscopy Female Humans Intestinal Diseases Aged Neural Networks, Computer Intestine, Small Angiodysplasia Aged, 80 and over Algorithms Sensitivity and Specificity Male
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Digital Image Analysis with Fully Connected Convolutional Neural Network to Facilitate Hysteroscopic Fibroid Resection.

Gynecologic and obstetric investigation Jul 5, 2018
AIMS: The study aimed to determine the accuracy of deep neural network in identifying the plane between myoma and normal myometrium.
Myometrium Image Processing, Computer-Assisted Predictive Value of Tests Leiomyoma Humans Hysteroscopy Neural Networks, Computer Uterine Myomectomy Retrospective Studies Female Adult
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Machine learning models to predict the progression from early to late stages of papillary renal cell carcinoma.

Computers in biology and medicine Jun 28, 2018
Papillary Renal Cell Carcinoma (PRCC) is a heterogeneous disease with variations in disease progression and clinical outcomes. The advent of next generation sequencing techniques (NGS) has generated data from patients that can be analysed to develop ...
Models, Biological Humans Kidney Neoplasms Disease Progression Machine Learning Carcinoma, Renal Cell Transcriptome Female Sequence Analysis, RNA Male Gene Expression Regulation, Neoplastic Predictive Value of Tests
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A meta-learning framework using representation learning to predict drug-drug interaction.

Journal of biomedical informatics Jun 26, 2018
MOTIVATION: Predicting Drug-Drug Interaction (DDI) has become a crucial step in the drug discovery and development process, owing to the rise in the number of drugs co-administered with other drugs. Consequently, the usage of computational methods fo...
Drug Design Computational Biology Drug Development Predictive Value of Tests Pharmaceutical Preparations Drug Interactions Software Supervised Machine Learning Algorithms Drug-Related Side Effects and Adverse Reactions Probability Technology, Pharmaceutical
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An Algorithm Based on Deep Learning for Predicting In-Hospital Cardiac Arrest.

Journal of the American Heart Association Jun 26, 2018
BACKGROUND: In-hospital cardiac arrest is a major burden to public health, which affects patient safety. Although traditional track-and-trigger systems are used to predict cardiac arrest early, they have limitations, with low sensitivity and high fal...
Inpatients Middle Aged Humans Reproducibility of Results Resuscitation Predictive Value of Tests Decision Support Techniques Risk Assessment Risk Factors Seoul Early Diagnosis Diagnosis, Computer-Assisted Prognosis Aged Vital Signs Deep Learning Retrospective Studies Adult Heart Arrest Time Factors Female Male
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Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.

Gastroenterology Jun 18, 2018
BACKGROUND & AIMS: The benefit of colonoscopy for colorectal cancer prevention depends on the adenoma detection rate (ADR). The ADR should reflect the adenoma prevalence rate, which is estimated to be higher than 50% in the screening-age population. ...
Humans Neural Networks, Computer Machine Learning Colonic Polyps Video Recording ROC Curve Image Interpretation, Computer-Assisted Prognosis Early Detection of Cancer Observer Variation Reproducibility of Results Predictive Value of Tests Adenomatous Polyps Colorectal Neoplasms Area Under Curve Colonoscopy Feasibility Studies Diagnosis, Computer-Assisted
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