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Wounds, Penetrating

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Machine Learning Models for Prediction of Reinjury After Penetrating Trauma.

JAMA surgery 29049476
This study compares several machine learning models for prediction of reinjury after penetrating trauma.
Databases, Factual Forecasting Humans Machine Learning Mental Disorders Models, Theoretical Patient Readmission Recurrence Self-Injurious Behavior Suicide United States Wounds, Penetrating
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Trauma outcome predictor: An artificial intelligence interactive smartphone tool to predict outcomes in trauma patients.

The journal of trauma and acute care surgery 33755641
BACKGROUND: Classic risk assessment tools often treat patients' risk factors as linear and additive. Clinical reality suggests that the presence of certain risk factors can alter the impact of other factors; in other words, risk modeling is not linea...
Adult Aged Artificial Intelligence Databases, Factual Decision Support Techniques Emergencies Female Hospital Mortality Humans Injury Severity Score Male Middle Aged Predictive Value of Tests Risk Assessment Risk Factors Smartphone United States Wounds, Nonpenetrating Wounds, Penetrating
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Development of a Machine Learning-Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma.

JAMA surgery 37610746
IMPORTANCE: The use of artificial intelligence (AI) in clinical medicine risks perpetuating existing bias in care, such as disparities in access to postinjury rehabilitation services.
Adult Black or African American Female Health Services Accessibility Healthcare Disparities Humans Machine Learning Male Middle Aged Patient Discharge United States White Wounds, Penetrating
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