[HTML][HTML] Use of artificial intelligence in paediatric anaesthesia: a systematic review

R Antel, E Sahlas, G Gore, P Ingelmo - BJA open, 2023‏ - Elsevier
Objectives Although the development of artificial intelligence (AI) technologies in medicine
has been significant, their application to paediatric anaesthesia is not well characterised. As …

Augmented intelligence in pediatric anesthesia and pediatric critical care

M Görges, JM Ansermino - Current Opinion in Anesthesiology, 2020‏ - journals.lww.com
Most studies focusing on artificial intelligence demonstrate good performance on prediction
or classification, whether they use traditional statistical tools or novel machine-learning …

Utility of vital signs, heart rate variability and complexity, and machine learning for identifying the need for lifesaving interventions in trauma patients

NT Liu, JB Holcomb, CE Wade, MI Darrah, J Salinas - Shock, 2014‏ - journals.lww.com
To date, no studies have attempted to utilize data from a combination of vital signs, heart rate
variability and complexity (HRV, HRC), as well as machine learning (ML), for identifying the …

Toward automated instructor pilots in legacy Air Force systems: Physiology-based flight difficulty classification via machine learning

WN Caballero, N Gaw, PR Jenkins… - Expert Systems with …, 2023‏ - Elsevier
Abstract The United States Air Force (USAF) is struggling to train enough pilots to meet
operational requirements. Technology has advanced rapidly over the last 70 years but …

A qualitative study of expert and team cognition on complex patients in the pediatric intensive care unit

JW Custer, E White, JC Fackler, Y **ao… - Pediatric Critical Care …, 2012‏ - journals.lww.com
Objectives: To understand expert and team cognition of complex patients in the pediatric
intensive care unit through the use of cognitive task analysis. Design: Qualitative study with …

Wireless technology in the evolution of patient monitoring on general hospital wards

R Sahandi, S Noroozi, G Roushan… - Journal of medical …, 2010‏ - Taylor & Francis
The evolution of patient monitoring on general hospital wards is discussed. Patients on
general wards are monitored according to the severity of their conditions, which can be …

Using modified multivariate bag-of-words models to classify physiological data

P Ordonez, T Armstrong, T Oates… - 2011 IEEE 11th …, 2011‏ - ieeexplore.ieee.org
In this paper we present two novel multivariate time series representations to classify
physiological data of different lengths. The representations may be applied to any group of …

Computational modelling of cardiovascular pathophysiology to risk stratify commercial spaceflight

PD Morris, RA Anderton, K Marshall-Goebel… - Nature Reviews …, 2024‏ - nature.com
For more than 60 years, humans have travelled into space. Until now, the majority of
astronauts have been professional, government agency astronauts selected, in part, for their …

[HTML][HTML] Integrating monitor alarms with laboratory test results to enhance patient deterioration prediction

Y Bai, DH Do, PRE Harris, D Schindler… - Journal of biomedical …, 2015‏ - Elsevier
Patient monitors in modern hospitals have become ubiquitous but they generate an
excessive number of false alarms causing alarm fatigue. Our previous work showed that …

Dynamic three-dimensional scoring of cerebral perfusion pressure and intracranial pressure provides a brain trauma index that predicts outcome in patients with …

S Kahraman, P Hu, DM Stein… - Journal of Trauma …, 2011‏ - journals.lww.com
Background: Data on intracranial pressure (ICP) and cerebral perfusion pressure (CPP)
guide therapy in severe traumatic brain injury (TBI), but current linear analytic methods are …