Adopting machine learning to predict ICU delirium.

Publication date: Jul 26, 2024

With neuropsychiatric complications recognized among COVID-19 patients translating into significant morbidity, we explore the current state-of-the-art for auto Machine Learning (ML) to predict ICU delirium among severe COVID-19 patients which has been identified as a significant predictor of cognitive decline among such patients. Such optimally developed ML models can provide instantaneous, accurate and precise risk-stratification predictions, allowing neurology clinicians to take an informed decision regarding the advanced neuropsychiatric management for severe COVID-19 patients. Such incorporation of ML into the relevant management protocols has the potential to significantly curtail the morbidity and mortality associated with the once-in-a-century global public health catastrophe.

Concepts Keywords
Covid Adopting
Instantaneous Complications
Models Covid
Mortality Delirium
Neuropsychiatric Icu
Learning
Management
Morbidity
Neuropsychiatric
Patients
Predict
Recognized
Severe
Significant
Translating

Semantics

Type Source Name
disease MESH delirium
disease MESH complications
disease MESH COVID-19
disease MESH morbidity
disease MESH cognitive decline

Original Article

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