A systematic literature review of predicting patient discharges using statistical methods and machine learning

M Pahlevani, M Taghavi, P Vanberkel - Health Care Management Science, 2024 - Springer
Discharge planning is integral to patient flow as delays can lead to hospital-wide
congestion. Because a structured discharge plan can reduce hospital length of stay while …

Stroke mortality prediction using machine learning: systematic review

L Schwartz, R Anteby, E Klang, S Soffer - Journal of the Neurological …, 2023 - Elsevier
Background and aims Accurate prognostication of stroke may help in appropriate therapy
and rehabilitation planning. In the past few years, several machine learning (ML) algorithms …

From admission to discharge: predicting national institutes of health stroke scale progression in stroke patients using biomarkers and explainable machine learning

A Gkantzios, C Kokkotis, D Tsiptsios… - Journal of Personalized …, 2023 - mdpi.com
As a result of social progress and improved living conditions, which have contributed to a
prolonged life expectancy, the prevalence of strokes has increased and has become a …

Risk factor identification and prediction models for prolonged length of stay in hospital after acute ischemic stroke using artificial neural networks

CC Yang, OA Bamodu, L Chan, JH Chen… - Frontiers in …, 2023 - frontiersin.org
Background Accurate estimation of prolonged length of hospital stay after acute ischemic
stroke provides crucial information on medical expenditure and subsequent disposition. This …

Development and validation of a machine learning-based prognostic risk stratification model for acute ischemic stroke

K Wang, T Hong, W Liu, C Xu, C Yin, H Liu, X Wei… - Scientific Reports, 2023 - nature.com
Acute ischemic stroke (AIS) is a most prevalent cause of serious long-term disability
worldwide. Accurate prediction of stroke prognosis is highly valuable for effective …

[HTML][HTML] Machine learning for storage duration based on volatile organic compounds emitted from'Jukhyang'and'Merry Queen'strawberries during post-harvest storage

E Do, M Kim, DY Ko, M Lee, C Lee, KM Ku - Postharvest Biology and …, 2024 - Elsevier
Abstract Strawberry (Fragaria× ananassa Duch.) is a widely favored horticultural crop
renowned for its unique taste and flavor. To develop an accurate predictive model for …

Predicting short and long-term mortality after acute ischemic stroke using EHR

V Abedi, V Avula, SM Razavi, S Bavishi… - Journal of the …, 2021 - Elsevier
Objective Despite improvements in treatment, stroke remains a leading cause of mortality
and long-term disability. In this study, we leveraged administrative data to build predictive …

Hospital length of stay and 30-day mortality prediction in stroke: a machine learning analysis of 17,000 ICU admissions in Brazil

P Kurtz, IT Peres, M Soares, JIF Salluh, FA Bozza - Neurocritical Care, 2022 - Springer
Background Hospital length of stay and mortality are associated with resource use and
clinical severity, respectively, in patients admitted to the intensive care unit (ICU) with acute …

Evaluation of blood biomarkers and parameters for the prediction of stroke survivors' functional outcome upon discharge utilizing explainable machine learning

A Gkantzios, C Kokkotis, D Tsiptsios, S Moustakidis… - Diagnostics, 2023 - mdpi.com
Despite therapeutic advancements, stroke remains a leading cause of death and long-term
disability. The quality of current stroke prognostic models varies considerably, whereas …

The Artificial Intelligence Revolution in Stroke Care: A Decade of Scientific Evidence in Review

K El Naamani, B Musmar, N Gupta, O Ikhdour… - World Neurosurgery, 2024 - Elsevier
Background The emergence of artificial intelligence (AI) has significantly influenced the
diagnostic evaluation of stroke and has revolutionized acute stroke care delivery. The …