The journal of trauma and acute care surgery
Oct 1, 2020
BACKGROUND: Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learning-based model to predict mortality using Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework. We...
The journal of trauma and acute care surgery
Aug 1, 2020
BACKGROUND: Compensatory reserve measurement (CRM) is a novel noninvasive monitoring technology designed to assess physiologic reserve using feature interrogation of arterial pulse waveforms. This study was conducted to validate clinically relevant C...
The journal of trauma and acute care surgery
Jul 1, 2019
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 ...
The journal of trauma and acute care surgery
Aug 1, 2018
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.
The Journal of head trauma rehabilitation
Jan 1, 2018
OBJECTIVE: To investigate the use of a robotic assessment tool to quantify sensorimotor, visuospatial attention, and executive function impairments in individuals with traumatic brain injury (TBI).
BACKGROUND: Cell free DNA (cfDNA) was recently suggested as a new marker of sepsis and poor outcome in ICU patients. Procalcitonin has also been the focus of attention as an early marker for systemic inflammation and sepsis.
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