ArticleDiagnostics (Basel, Switzerland)2021
Machine Learning-Based Three-Month Outcome Prediction in Acute Ischemic Stroke: A Single Cerebrovascular-Specialty Hospital Study in South Korea.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Machine learning models of segmentation in acute ischemic stroke: a systematic review and meta-analysis.Biomedical engineering online · 2026Pooled it
- Machine learning prediction of motor function in chronic stroke patients: a systematic review and meta-analysis.Frontiers in neurology · 2023Pooled it
- Predictive performance of machine learning models in acute ischemic stroke: a systematic review and meta-analysis.Frontiers in neurologyPooled it
- Machine Learning-Based Prediction of Transition to Functional Upper Limb Recovery After Intensive Inpatient Rehabilitation in Early Subacute Stroke.Journal of clinical medicine · 2026Article
- Machine learning-based study of the predictors of clinically important change in patient-reported outcomes in bilateral upper-limb function in patients receiving robotic stroke rehabilitation.Frontiers in rehabilitation sciences · 2026Article
- AI post-intervention operational and functional outcomes prediction in ischemic stroke patients using MRIs.BMC medical imaging · 2025Article
- Dynamic, Interpretable, Machine Learning-Based Outcome Prediction as a New Emerging Opportunity in Acute Ischemic Stroke Patient Care: A Proof-of-Concept Study.Stroke research and treatment · 2025Article
- RGX Ensemble Model for Advanced Prediction of Mortality Outcomes in Stroke Patients.BME frontiers · 2024Article
- In-hospital fall prediction using machine learning algorithms and the Morse fall scale in patients with acute stroke: a nested case-control study.BMC medical informatics and decision making · 2023Article
- Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application.Internal and emergency medicine · 2023Article
- [An interpretable machine learning-based prediction model for risk of death for patients with ischemic stroke in intensive care unit].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2023Article
- Predicting Arm Nonuse in Individuals with Good Arm Motor Function after Stroke Rehabilitation: A Machine Learning Study.International journal of environmental research and public health · 2023Article
- Predicting patient-reported outcome of activities of daily living in stroke rehabilitation: a machine learning study.Journal of neuroengineering and rehabilitation · 2023Article
- Clustering and prediction of long-term functional recovery patterns in first-time stroke patients.Frontiers in neurology · 2023Article
- Longitudinal Data to Enhance Dynamic Stroke Risk Prediction.Healthcare (Basel, Switzerland) · 2022Article
- An Explainable Machine Learning Pipeline for Stroke Prediction on Imbalanced Data.Diagnostics (Basel, Switzerland) · 2022Article
- Development and Validation of an Insulin Resistance Model for a Population with Chronic Kidney Disease Using a Machine Learning Approach.Nutrients · 2022Article
- Development and Validation of an Insulin Resistance Predicting Model Using a Machine-Learning Approach in a Population-Based Cohort in Korea.Diagnostics (Basel, Switzerland) · 2022Article
- Machine Learning-Based Prediction of Subsequent Vascular Events After 6 Months in Chinese Patients with Minor Ischemic Stroke.International journal of general medicine · 2022Article
- Machine Learning Consensus Clustering Approach for Hospitalized Patients with Dysmagnesemia.Diagnostics (Basel, Switzerland) · 2021Article
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Authors and funding
12 authors.
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Abstract
backgroundFunctional outcomes after acute ischemic stroke are of great concern to patients and their families, as well as physicians and surgeons who make the clinical decisions. We developed machine learning (ML)-based functional outcome prediction models in acute ischemic stroke.
methodsThis retrospective study used a prospective cohort database. A total of 1066 patients with acute ischemic stroke between January 2019 and March 2021 were included. Variables such as demographic factors, stroke-related factors, laboratory findings, and comorbidities were utilized at the time of admission. Five ML algorithms were applied to predict a favorable functional outcome (modified Rankin Scale 0 or 1) at 3 months after stroke onset.
resultsRegularized logistic regression showed the best performance with an area under the receiver operating characteristic curve (AUC) of 0.86. Support vector machines represented the second-highest AUC of 0.85 with the highest F1-score of 0.86, and finally, all ML models applied achieved an AUC > 0.8. The National Institute of Health Stroke Scale at admission and age were consistently the top two important variables for generalized logistic regression, random forest, and extreme gradient boosting models.
conclusionsML-based functional outcome prediction models for acute ischemic stroke were validated and proven to be readily applicable and useful.
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