AIMC Topic:
Predictive Value of Tests

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Combining Biomarkers with EMR Data to Identify Patients in Different Phases of Sepsis.

Scientific reports Sep 7, 2017
Sepsis is a leading cause of death and is the most expensive condition to treat in U.S. hospitals. Despite targeted efforts to automate earlier detection of sepsis, current techniques rely exclusively on using either standard clinical data or novel b...
Sepsis ROC Curve United States Predictive Value of Tests Electronic Data Processing Humans Machine Learning Decision Support Techniques Biomarkers Electronic Health Records
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Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing.

Digestive diseases and sciences Aug 31, 2017
INTRODUCTION: Natural language processing is a powerful technique of machine learning capable of maximizing data extraction from complex electronic medical records.
Data Mining United States Department of Veterans Affairs Veterans Health Fatty Liver United States Magnetic Resonance Imaging Predictive Value of Tests Natural Language Processing Prognosis Tomography, X-Ray Computed Electronic Health Records Ultrasonography Humans Algorithms Databases, Factual
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Using Machine Learning to Define the Association between Cardiorespiratory Fitness and All-Cause Mortality (from the Henry Ford Exercise Testing Project).

The American journal of cardiology Aug 30, 2017
Previous studies have demonstrated that cardiorespiratory fitness is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined ca...
Retrospective Studies Female Male Cardiovascular Diseases Middle Aged Humans Machine Learning Algorithms Forecasting Cardiorespiratory Fitness Michigan Risk Assessment Predictive Value of Tests Cause of Death Exercise Test Exercise Tolerance
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Predicting symptomatic cerebral vasospasm after aneurysmal subarachnoid hemorrhage with an artificial neural network in a pediatric population.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery Aug 29, 2017
PURPOSE: Artificial neural networks (ANN) are increasingly applied to complex medical problem solving algorithms because their outcome prediction performance is superior to existing multiple regression models. ANN can successfully identify symptomati...
Humans Neural Networks, Computer Retrospective Studies Female Male Adolescent Subarachnoid Hemorrhage Vasospasm, Intracranial Aneurysm, Ruptured Child, Preschool Child Population Surveillance Predictive Value of Tests
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Early Colorectal Cancer Detected by Machine Learning Model Using Gender, Age, and Complete Blood Count Data.

Digestive diseases and sciences Aug 23, 2017
BACKGROUND: Machine learning tools identify patients with blood counts indicating greater likelihood of colorectal cancer and warranting colonoscopy referral.
Sex Factors Referral and Consultation Blood Cell Count Odds Ratio Early Detection of Cancer Predictive Value of Tests Area Under Curve Registries Data Mining Colonoscopy Diagnosis, Computer-Assisted ROC Curve Age Factors Algorithms Female Reproducibility of Results Risk Factors Aged Aged, 80 and over Adult Colorectal Neoplasms Male Middle Aged Humans Machine Learning
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An Ameliorated Prediction of Drug-Target Interactions Based on Multi-Scale Discrete Wavelet Transform and Network Features.

International journal of molecular sciences Aug 16, 2017
The prediction of drug-target interactions (DTIs) via computational technology plays a crucial role in reducing the experimental cost. A variety of state-of-the-art methods have been proposed to improve the accuracy of DTI predictions. In this paper,...
Drug Interactions Wavelet Analysis Humans Animals Support Vector Machine Predictive Value of Tests Models, Biological
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Enhancement of hepatitis virus immunoassay outcome predictions in imbalanced routine pathology data by data balancing and feature selection before the application of support vector machines.

BMC medical informatics and decision making Aug 14, 2017
BACKGROUND: Data mining techniques such as support vector machines (SVMs) have been successfully used to predict outcomes for complex problems, including for human health. Much health data is imbalanced, with many more controls than positive cases.
Support Vector Machine Predictive Value of Tests Immunoassay Hepatitis C Data Mining Humans Hepatitis B
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Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of Atherosclerosis.

Circulation research Aug 9, 2017
RATIONALE: Machine learning may be useful to characterize cardiovascular risk, predict outcomes, and identify biomarkers in population studies.
Survival Rate Male Cardiovascular Diseases Middle Aged Cohort Studies Humans Machine Learning Female Aged Aged, 80 and over Follow-Up Studies Predictive Value of Tests Atherosclerosis Ethnicity
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Measuring Functional Arm Movement after Stroke Using a Single Wrist-Worn Sensor and Machine Learning.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Aug 4, 2017
BACKGROUND AND PURPOSE: Trials of restorative therapies after stroke and clinical rehabilitation require relevant and objective efficacy end points; real-world upper extremity (UE) functional use is an attractive candidate. We present a novel, inexpe...
Video Recording Fitness Trackers Actigraphy Movement Upper Extremity Stroke Feasibility Studies Activities of Daily Living Acceleration Adult Biomechanical Phenomena Male Middle Aged Case-Control Studies Time Factors Health Status Predictive Value of Tests Equipment Design Signal Processing, Computer-Assisted Humans Machine Learning Female Reproducibility of Results Aged
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Gaussian process classification of superparamagnetic relaxometry data: Phantom study.

Artificial intelligence in medicine Jul 24, 2017
MOTIVATION: Superparamagnetic relaxometry (SPMR) is an emerging technology that holds potential for use in early cancer detection. Measurement of the magnetic field after the excitation of cancer-bound superparamagnetic iron oxide nanoparticles (SPIO...
Early Detection of Cancer Predictive Value of Tests Magnetite Nanoparticles Signal-To-Noise Ratio Magnetics Neoplasms, Experimental Phantoms, Imaging Normal Distribution Numerical Analysis, Computer-Assisted Animals Image Processing, Computer-Assisted Mice Contrast Media Magnetic Resonance Imaging Machine Learning Algorithms Computer Simulation Reproducibility of Results
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