AIMC Topic:
Predictive Value of Tests

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Machine Learning to Predict Anti-Tumor Necrosis Factor Drug Responses of Rheumatoid Arthritis Patients by Integrating Clinical and Genetic Markers.

Arthritis & rheumatology (Hoboken, N.J.) Nov 4, 2019
OBJECTIVE: Accurate prediction of treatment responses in rheumatoid arthritis (RA) patients can provide valuable information on effective drug selection. Anti-tumor necrosis factor (anti-TNF) drugs are an important second-line treatment after methotr...
Severity of Illness Index Arthritis, Rheumatoid Polymorphism, Single Nucleotide Treatment Outcome Regression Analysis Female Reproducibility of Results Male Middle Aged Outcome Assessment, Health Care Antirheumatic Agents Humans Normal Distribution Machine Learning Predictive Value of Tests Tumor Necrosis Factor-alpha Etanercept Infliximab Certolizumab Pegol Genetic Markers Methotrexate Adalimumab
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Statistical and machine learning methodology for abdominal aortic aneurysm prediction from ultrasound screenings.

Echocardiography (Mount Kisco, N.Y.) Nov 4, 2019
A method of analysis of a database of patients (n = 10 329) screened for an abdominal aortic aneurysm (AAA) is presented. Self-reported height, weight, age, gender, ethnicity, and parameters "Heart Problems," "Hypertension," "High Cholesterol," "Diab...
Humans Machine Learning Retrospective Studies United States Mass Screening Follow-Up Studies Predictive Value of Tests Aortic Aneurysm, Abdominal Age Distribution Sex Distribution Female Male Risk Factors Middle Aged Aged Prevalence Aged, 80 and over Incidence Ultrasonography
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Intravascular ultrasound-based machine learning for predicting fractional flow reserve in intermediate coronary artery lesions.

Atherosclerosis Nov 2, 2019
BACKGROUND AND AIMS: Intravascular ultrasound (IVUS)-derived morphological criteria are poor predictors of the functional significance of intermediate coronary stenosis. IVUS-based supervised machine learning (ML) algorithms were developed to identif...
Fractional Flow Reserve, Myocardial Middle Aged Predictive Value of Tests Ultrasonography, Interventional Coronary Stenosis Humans Machine Learning Retrospective Studies Female Aged Male
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Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial.

JMIR mHealth and uHealth Nov 1, 2019
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a major public health burden. Self-management of diabetes including maintaining a healthy lifestyle is essential for glycemic control and to prevent diabetes complications. Mobile-based health data can p...
Humans Forecasting Female Self-Management Diabetes Mellitus, Type 2 Predictive Value of Tests Male Middle Aged Deep Learning Pilot Projects Blood Glucose
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Evaluation of Machine Learning Algorithms for Predicting Readmission After Acute Myocardial Infarction Using Routinely Collected Clinical Data.

The Canadian journal of cardiology Oct 25, 2019
BACKGROUND: The ability to predict readmission accurately after hospitalization for acute myocardial infarction (AMI) is limited in current statistical models. Machine-learning (ML) methods have shown improved predictive ability in various clinical c...
Risk Assessment Time Factors Female Canada Risk Factors Predictive Value of Tests Hospitalization Myocardial Infarction Male Patient Readmission Middle Aged Humans Machine Learning Algorithms Prognosis
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Analysis of substance use and its outcomes by machine learning I. Childhood evaluation of liability to substance use disorder.

Drug and alcohol dependence Oct 22, 2019
BACKGROUND: Substance use disorder (SUD) exacts enormous societal costs in the United States, and it is important to detect high-risk youths for prevention. Machine learning (ML) is the method to find patterns and make prediction from data. We hypoth...
Predictive Value of Tests Substance-Related Disorders Outcome Assessment, Health Care Psychological Techniques Humans Machine Learning Severity of Illness Index Adolescent Child ROC Curve Longitudinal Studies Female Reproducibility of Results Young Adult Adult Male
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Data-efficient deep learning of radiological image data for outcome prediction after endovascular treatment of patients with acute ischemic stroke.

Computers in biology and medicine Oct 22, 2019
Treatment selection is becoming increasingly more important in acute ischemic stroke patient care. Clinical variables and radiological image biomarkers (old age, pre-stroke mRS, NIHSS, occlusion location, ASPECTS, among others) have an important role...
Aged, 80 and over Male Middle Aged Postoperative Complications Predictive Value of Tests Registries Stroke Brain Ischemia Endovascular Procedures Computed Tomography Angiography Humans Neural Networks, Computer Prospective Studies Cerebral Angiography Female Aged
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A speckle-tracking strain-based artificial neural network model to differentiate cardiomyopathy type.

Scandinavian cardiovascular journal : SCJ Oct 18, 2019
In heart failure, invasive angiography is often employed to differentiate ischaemic from non-ischaemic cardiomyopathy. We aim to examine the predictive value of echocardiographic strain features alone and in combination with other features to differ...
Predictive Value of Tests Heart Failure Image Interpretation, Computer-Assisted Cardiomyopathies Stroke Volume Echocardiography Middle Aged Diagnosis, Computer-Assisted Diagnosis, Differential Reproducibility of Results Aged Male Ventricular Function, Left Humans Neural Networks, Computer Prognosis Retrospective Studies Female
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Investigating Risk Factors and Predicting Complications in Deep Brain Stimulation Surgery with Machine Learning Algorithms.

World neurosurgery Oct 18, 2019
BACKGROUND: Deep brain stimulation (DBS) surgery is an option for patients experiencing medically resistant neurologic symptoms. DBS complications are rare; finding significant predictors requires a large number of surgeries. Machine learning algorit...
Middle Aged Postoperative Complications Predictive Value of Tests Registries Deep Brain Stimulation Retrospective Studies Humans Female Machine Learning Risk Factors Algorithms Aged Male
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Predicting diabetes second-line therapy initiation in the Australian population via time span-guided neural attention network.

PloS one Oct 18, 2019
INTRODUCTION: The first line of treatment for people with Diabetes mellitus is metformin. However, over the course of the disease metformin may fail to achieve appropriate glycemic control, and a second-line therapy may become necessary. In this pape...
Predictive Value of Tests Models, Biological Metformin Female Male Humans Diabetes Mellitus Neural Networks, Computer Australia Machine Learning
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