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Trauma Centers

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Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT) Study.

PloS one
Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of...

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
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...

Artificial neural networks: Predicting head CT findings in elderly patients presenting with minor head injury after a fall.

The American journal of emergency medicine
OBJECTIVES: To construct an artificial neural network (ANN) model that can predict the presence of acute CT findings with both high sensitivity and high specificity when applied to the population of patients≄age 65years who have incurred minor head i...

Communication with Orthopedic Trauma Patients via an Automated Mobile Phone Messaging Robot.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
BACKGROUND: Communication with orthopedic trauma patients is traditionally problematic with low response rates (RRs). The purpose of this investigation was to (1) evaluate the feasibility of communicating with orthopedic trauma patients postoperative...

Artificial intelligence can predict daily trauma volume and average acuity.

The journal of trauma and acute care surgery
BACKGROUND: The goal of this study was to integrate temporal and weather data in order to create an artificial neural network (ANN) to predict trauma volume, the number of emergent operative cases, and average daily acuity at a Level I trauma center.

A natural language processing algorithm to extract characteristics of subdural hematoma from head CT reports.

Emergency radiology
PURPOSE: Subdural hematoma (SDH) is the most common form of traumatic intracranial hemorrhage, and radiographic characteristics of SDH are predictive of complications and patient outcomes. We created a natural language processing (NLP) algorithm to e...

Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Alcohol misuse is present in over a quarter of trauma patients. Information in the clinical notes of the electronic health record of trauma patients may be used for phenotyping tasks with natural language processing (NLP) and supervised ma...

Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: A multicenter study.

The journal of trauma and acute care surgery
BACKGROUND: Trauma has long been considered unpredictable. Artificial neural networks (ANN) have recently shown the ability to predict admission volume, acuity, and operative needs at a single trauma center with very high reliability. This model has ...

Exploring the Role of Artificial Intelligence in an Emergency and Trauma Radiology Department.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Emergency and trauma radiologists, emergency department's physicians and nurses, researchers, departmental leaders, and health policymakers have attempted to discover efficient approaches to enhance the provision of quality patient care. There are in...

Dynamic impact of transfusion ratios on outcomes in severely injured patients: Targeted machine learning analysis of the Pragmatic, Randomized Optimal Platelet and Plasma Ratios randomized clinical trial.

The journal of trauma and acute care surgery
BACKGROUND: Massive transfusion protocols to treat postinjury hemorrhage are based on predefined blood product transfusion ratios followed by goal-directed transfusion based on patient's clinical evolution. However, it remains unclear how these trans...