AIMC Topic: Predictive Value of Tests
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Automated Extraction of VTE Events From Narrative Radiology Reports in Electronic Health Records: A Validation Study.
Medical care
Oct 1, 2017
BACKGROUND: Surveillance of venous thromboembolisms (VTEs) is necessary for improving patient safety in acute care hospitals, but current detection methods are inaccurate and inefficient. With the growing availability of clinical narratives in an ele...
Prediction of Anti-VEGF Treatment Requirements in Neovascular AMD Using a Machine Learning Approach.
Investigative ophthalmology & visual science
Jun 1, 2017
PURPOSE: The purpose of this study was to predict low and high anti-VEGF injection requirements during a pro re nata (PRN) treatment, based on sets of optical coherence tomography (OCT) images acquired during the initiation phase in neovascular AMD.
Macular Degeneration
Ranibizumab
Subretinal Fluid
Choroidal Neovascularization
Angiogenesis Inhibitors
Visual Acuity
Predictive Value of Tests
Tomography, Optical Coherence
Vascular Endothelial Growth Factor A
Humans
Middle Aged
Aged
Machine Learning
Pilot Projects
Aged, 80 and over
Female
ROC Curve
Male
Community-Acquired Pneumonia Case Validation in an Anonymized Electronic Medical Record-Linked Expert System.
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
May 15, 2017
An electronic anonymized patient portal analysis using radiographic reports and admission and discharge diagnoses had sensitivity, specificity, positive predictive value, and negative predictive value of 84.7%, 78.2%, 75%, and 87%, respectively, for ...
Machine Learning of the Progression of Intermediate Age-Related Macular Degeneration Based on OCT Imaging.
Investigative ophthalmology & visual science
May 1, 2017
PURPOSE: To develop a data-driven interpretable predictive model of incoming drusen regression as a sign of disease activity and identify optical coherence tomography (OCT) biomarkers associated with its risk in intermediate age-related macular degen...
Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation.
Transplantation
Apr 1, 2017
BACKGROUND: The ability to predict graft failure or primary nonfunction at liver transplant decision time assists utilization of scarce resource of donor livers, while ensuring that patients who are urgently requiring a liver transplant are prioritiz...
Victoria
Adolescent
Time Factors
ROC Curve
Tissue Donors
Graft Survival
Patient Selection
Treatment Failure
Donor Selection
Predictive Value of Tests
Area Under Curve
Machine Learning
Liver Transplantation
Databases, Factual
Young Adult
Algorithms
Adult
Decision Support Techniques
Female
Male
Middle Aged
Reproducibility of Results
Humans
Risk Assessment
Risk Factors
Aged
Prediction of 30-Day All-Cause Readmissions in Patients Hospitalized for Heart Failure: Comparison of Machine Learning and Other Statistical Approaches.
JAMA cardiology
Feb 1, 2017
IMPORTANCE: Several attempts have been made at developing models to predict 30-day readmissions in patients with heart failure, but none have sufficient discriminatory capacity for clinical use. Machine-learning (ML) algorithms represent a novel appr...
Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma.
Oncotarget
Jan 31, 2017
RATIONALE: Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror ...
Disease Progression
Pilot Projects
Time Factors
Treatment Outcome
Glioma
Predictive Value of Tests
Positron Emission Tomography Computed Tomography
Neoplasm Grading
Magnetic Resonance Imaging
Cluster Analysis
Unsupervised Machine Learning
Aged
Adult
Brain Neoplasms
Male
Middle Aged
Humans
Radiographic Image Interpretation, Computer-Assisted
Retrospective Studies
Radiopharmaceuticals
Female
Disease-Free Survival
Reproducibility of Results
Kaplan-Meier Estimate
Tyrosine
A simplified chart for determining the initial loading dose of teicoplanin in critically ill patients.
Die Pharmazie
Jan 10, 2017
AIM OF THE STUDY: A simplified chart to determine the initial loading dose of teicoplanin (TEIC chart) for achieving the target trough concentration was developed. The aim of the present study was to evaluate the usefulness of this chart in criticall...
NT-proBNP Predicts All-Cause Mortality in a Population of Insurance Applicants, Follow-up Analysis and Further Observations.
Journal of insurance medicine (New York, N.Y.)
Jan 1, 2017
OBJECTIVE: - Further refine the independent value of NT-proBNP, accounting for the impact of other test results, in predicting all-cause mortality for individual life insurance applicants with and without heart disease.
A Performance Comparison on the Machine Learning Classifiers in Predictive Pathology Staging of Prostate Cancer.
Studies in health technology and informatics
Jan 1, 2017
This study objectives to investigate a range of Partin table and several machine learning methods for pathological stage prediction and assess them with respect to their predictive model performance based on Koreans data. The data was used SPCDB and ...
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