首页|Rajshahi University of Engineering & Technology Reports Findings in Stroke (A stroke prediction framework using explainable ensemble learning)
Rajshahi University of Engineering & Technology Reports Findings in Stroke (A stroke prediction framework using explainable ensemble learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Cerebrovascular Diseas es and Conditions - Stroke is the subject of a report. According to news reporti ng from Rajshahi, Bangladesh, by NewsRx journalists, research stated, "The death of brain cells occurs when blood flow to a particular area of the brain is abru ptly cut off, resulting in a stroke. Early recognition of stroke symptoms is ess ential to prevent strokes and promote a healthy lifestyle." The news correspondents obtained a quote from the research from the Rajshahi Uni versity of Engineering & Technology, "FAST tests (looking for abno rmalities in the face, arms, and speech) have limitations in reliability and acc uracy for diagnosing strokes. This research employs machine learning (ML) techni ques to develop and assess multiple ML models to establish a robust stroke risk prediction framework. This research uses a stacking-based ensemble method to sel ect the best three machine learning (ML) models and combine their collective int elligence. An empirical evaluation of a publicly available stroke prediction dat aset demonstrates the superior performance of the proposed stacking-based ensemb le model, with only one misclassification. The experimental results reveal that the proposed stacking model surpasses other state-of-the-art research, achieving accuracy, precision, F1-score of 99.99%, recall of 100% , receiver operating characteristics (ROC), Mathews correlation coefficient (MCC ), and Kappa scores 1.0. Furthermore, Shapley's Additive Explanations (SHAP) are employed to analyze the predictions of the black-box machine learning (ML) mode ls. The findings highlight that age, BMI, and glucose level are the most signifi cant risk factors for stroke prediction."
RajshahiBangladeshAsiaCerebrovascu lar Diseases and ConditionsCyborgsEmerging TechnologiesHealth and MedicineMachine LearningRisk and PreventionStroke
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