AIMC Topic: Critical Care

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[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...

Text Processing for Detection of Fungal Ocular Involvement in Critical Care Patients: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Fungal ocular involvement can develop in patients with fungal bloodstream infections and can be vision-threatening. Ocular involvement has become less common in the current era of improved antifungal therapies. Retrospectively determining...