International journal of injury control and safety promotion
Sep 8, 2016
Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too...
Public health reports (Washington, D.C. : 1974)
Aug 22, 2016
OBJECTIVE: The purpose of this study was to compare the rates of traumatic injury among five racial/ethnic groups in Arizona and to identify which mechanisms and intents of traumatic injury were predominant in each group.
Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society
Feb 4, 2016
Chronic nonhealing wounds have a prevalence of 2% in the United States, and cost an estimated $50 billion annually. Accurate stratification of wounds for risk of slow healing may help guide treatment and referral decisions. We have applied modern mac...
Telemedicine helps to deliver health services electronically to patients with the advancement of communication systems and health informatics. Chronic wound (CW) detection and its healing rate assessment at remote distance is very much difficult due ...
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...
BACKGROUND: Tumor necrosis factor (TNF)-α variant is closely linked to sepsis syndrome and mortality after severe trauma. We aimed to identify feature genes associated with the TNF rs1800629 A allele in trauma patients and help to direct them toward ...
BMC medical informatics and decision making
May 20, 2015
Narrative text is a useful way of identifying injury circumstances from the routine emergency department data collections. Automatically classifying narratives based on machine learning techniques is a promising technique, which can consequently redu...
We present prediction and variable importance (VIM) methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patie...
BACKGROUND: Predicting Posttraumatic Stress Disorder (PTSD) is a pre-requisite for targeted prevention. Current research has identified group-level risk-indicators, many of which (e.g., head trauma, receiving opiates) concern but a subset of survivor...
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