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Emergency Service, Hospital

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Utilization of machine learning for prediction of post-traumatic stress: a re-examination of cortisol in the prediction and pathways to non-remitting PTSD.

Translational psychiatry Mar 21, 2017
To date, studies of biological risk factors have revealed inconsistent relationships with subsequent post-traumatic stress disorder (PTSD). The inconsistent signal may reflect the use of data analytic tools that are ill equipped for modeling the comp...
Emergency Service, Hospital Norepinephrine Hydrocortisone Saliva Longitudinal Studies Blood Pressure Area Under Curve Urine Wounds and Injuries Psychological Trauma Receptors, Glucocorticoid Lymphocytes Heart Rate Adrenocorticotropic Hormone Linear Models Female Young Adult Adult Male Risk Assessment Stress Disorders, Post-Traumatic ROC Curve Support Vector Machine Humans Machine Learning Algorithms
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Will they participate? Predicting patients' response to clinical trial invitations in a pediatric emergency department.

Journal of the American Medical Informatics Association : JAMIA Apr 27, 2016
OBJECTIVE: (1) To develop an automated algorithm to predict a patient's response (ie, if the patient agrees or declines) before he/she is approached for a clinical trial invitation; (2) to assess the algorithm performance and the predictors on real-w...
Patient Participation Patient Acceptance of Health Care Machine Learning Algorithms Female Male Child Emergency Service, Hospital Hospitals, Pediatric Clinical Trials as Topic Humans
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Electronic medical record phenotyping using the anchor and learn framework.

Journal of the American Medical Informatics Association : JAMIA Apr 23, 2016
BACKGROUND: Electronic medical records (EMRs) hold a tremendous amount of information about patients that is relevant to determining the optimal approach to patient care. As medicine becomes increasingly precise, a patient's electronic medical record...
Machine Learning Phenotype Electronic Health Records Natural Language Processing Humans Area Under Curve Emergency Service, Hospital Databases as Topic Decision Making, Computer-Assisted
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Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine Apr 13, 2016
OBJECTIVE: Delayed diagnosis of Kawasaki disease (KD) may lead to serious cardiac complications. We sought to create and test the performance of a natural language processing (NLP) tool, the KD-NLP, in the identification of emergency department (ED) ...
Humans Electronic Health Records Sensitivity and Specificity Child Data Mining Mucocutaneous Lymph Node Syndrome Natural Language Processing Emergency Service, Hospital
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A Novel Tool for Evaluation of Mild Traumatic Brain Injury Patients in the Emergency Department: Does Robotic Assessment of Neuromotor Performance Following Injury Predict the Presence of Postconcussion Symptoms at Follow-up?

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine Mar 21, 2016
OBJECTIVES: Postconcussion symptoms (PCS) are a common complication of mild traumatic brain injury (TBI). Currently, there is no validated clinically available method to reliably predict at the time of injury who will subsequently develop PCS. The pu...
Young Adult Diagnostic Techniques, Neurological Robotics Adult Head Injuries, Closed Emergency Service, Hospital Middle Aged Sensitivity and Specificity Humans Post-Concussion Syndrome Observer Variation Urban Population Male Female Follow-Up Studies Brain Injuries
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Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine Feb 13, 2016
OBJECTIVES: Predictive analytics in emergency care has mostly been limited to the use of clinical decision rules (CDRs) in the form of simple heuristics and scoring systems. In the development of CDRs, limitations in analytic methods and concerns wit...
Hospitalization Emergency Service, Hospital Trauma Centers Aged Machine Learning Humans ROC Curve Male Retrospective Studies Aged, 80 and over Middle Aged Adult Electronic Health Records Decision Support Systems, Clinical Sepsis Female Logistic Models Hospital Mortality
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Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine Jan 14, 2016
BACKGROUND: The authors have previously demonstrated highly reliable automated classification of free-text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine lea...
Tomography, X-Ray Computed Humans Child Machine Learning Brain Injuries Natural Language Processing Decision Trees Emergency Service, Hospital
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Giant bladder (10,500 mL in volume) in the ED.

The American journal of emergency medicine Dec 21, 2015
Urinary Bladder, Neurogenic Male Humans Emergency Service, Hospital Tomography, X-Ray Computed Urinary Retention Aged Diabetic Neuropathies
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Automated Reconciliation of Radiology Reports and Discharge Summaries.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
We study machine learning techniques to automatically identify limb abnormalities (including fractures, dislocations and foreign bodies) from radiology reports. For patients presenting to the Emergency Room (ER) with suspected limb abnormalities (e.g...
Wounds and Injuries Humans Extremities Machine Learning Radiology Software Diagnostic Errors Radiology Information Systems Support Vector Machine Patient Discharge Summaries Natural Language Processing Emergency Service, Hospital
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Comparison of machine learning classifiers for influenza detection from emergency department free-text reports.

Journal of biomedical informatics Sep 16, 2015
Influenza is a yearly recurrent disease that has the potential to become a pandemic. An effective biosurveillance system is required for early detection of the disease. In our previous studies, we have shown that electronic Emergency Department (ED) ...
Humans Machine Learning Emergency Service, Hospital Influenza, Human
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