AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Critical Care

Showing 131 to 140 of 273 articles

Clear Filters

A Clinically Practical and Interpretable Deep Model for ICU Mortality Prediction with External Validation.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Deep learning models are increasingly studied in the field of critical care. However, due to the lack of external validation and interpretability, it is difficult to generalize deep learning models in critical care senarios. Few works have validated ...

[Artificial intelligence in neurocritical care].

Der Nervenarzt
Artificial intelligence (AI) has been introduced into medicine and an AI-assisted medicine will be the future that we should help to shape. In particular, supervised, unsupervised, and reinforcement learning will be the main methods to play a role in...

Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation.

Chest
BACKGROUND: Objective and early identification of hospitalized patients, and particularly those with novel coronavirus disease 2019 (COVID-19), who may require mechanical ventilation (MV) may aid in delivering timely treatment.

Predicting the need for intubation in the first 24 h after critical care admission using machine learning approaches.

Scientific reports
Early and accurate prediction of the need for intubation may provide more time for preparation and increase safety margins by avoiding high risk late intubation. This study evaluates whether machine learning can predict the need for intubation within...

Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU.

BMC medical informatics and decision making
BACKGROUND: Early and accurate identification of sepsis patients with high risk of in-hospital death can help physicians in intensive care units (ICUs) make optimal clinical decisions. This study aimed to develop machine learning-based tools to predi...