Adopting machine learning to predict ICU delirium

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.