Latest AI and machine learning research in critical care for healthcare professionals.
This paper proposes a novel methodology for automatic detection and localization of gastrointestinal...
The aim of this study was to evaluate the performance of models predicting in-hospital mortality in ...
BACKGROUND: Tidal hyperinflation can still occur with mechanical ventilation using low tidal volume ...
BACKGROUND: Finding potential drug targets is a crucial step in drug discovery and development. Rece...
BACKGROUND: - Acute respiratory failure is one of the most common problems encountered in intensive ...
Increasing learning ability from massive medical data and building learning methods robust to data q...
There is growing interest in applying machine learning methods to Electronic Medical Records (EMR). ...
Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuz...
BACKGROUND: Early identification of critically ill patients who will require prolonged mechanical ve...
BACKGROUND AND PURPOSE: There are two significant challenges when implementing functional-guided rad...
OBJECTIVE: Delirium is an important syndrome found in patients in the intensive care unit (ICU), how...
PURPOSE: To define the incidence of healthcare-associated ventriculitis and meningitis (HAVM) in the...
Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma ...
Existing drug discovery processes follow a reductionist model of "one-drug-one-gene-one-disease," wh...
BACKGROUND: Since early antimicrobial therapy is mandatory in septic patients, immediate diagnosis a...
Inulinase are industrial food enzymes which have gained much attention in recent scenario. In this s...
When training a machine learning algorithm for a supervised-learning task in some clinical applicati...
Accurate segmentation of perivascular spaces (PVSs) is an important step for quantitative study of P...
OBJECTIVE: The aim of this research was to develop a swallowing assessment method to help prevent as...
Electronic health records (EHRs) contain critical information useful for clinical studies. Early ass...
Multi-label learning is a common machine learning problem arising from numerous real-world applicati...