{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:13:32Z","timestamp":1761174812096,"version":"3.41.0"},"reference-count":43,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T00:00:00Z","timestamp":1736380800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Comput. Healthcare"],"published-print":{"date-parts":[[2025,1,31]]},"abstract":"<jats:p>According to the Global Health Observatory, stroke ranks second worldwide in causing dementia, right after Alzheimer\u2019s disease. The mortality rate linked to dementia resulting from stroke is high because symptoms are often recognized late, and stroke can be misinterpreted as other brain disorders. Early detection and diagnosis of stroke is crucial. Therefore, increasing awareness of stroke symptoms and implementing preventive measures becomes imperative. Prompt intervention by healthcare professionals can improve outcomes and reduce long-term complications of stroke.<\/jats:p>\n          <jats:p>The research introduces an innovative approach for early stroke prediction using a fuzzy scoring-based Decision Support System. This approach encompasses three main modules: Mind map-based Data Modeling, Fuzzy scoring computing, and Machine Learning (ML)-Based Decision System. By incorporating fuzzy logic, the approach extracts valuable knowledge from imprecise and uncertain data. Combining the fuzzy stroke risk model with a ML-based decision support system aims to enhance stroke prediction accuracy and improve preventive measures and patient outcomes. The approach\u2019s effectiveness was validated using real clinical data and tested with various ML classifiers, including K-Nearest Neighbor (KNN), Logistic Regression (LR), Decision Tree (DT), Artificial Neural Network (ANN), and Support Vector Machine (SVM). The results showed a strong correlation between stroke cases and computed risk-scoring values.<\/jats:p>\n          <jats:p>In comparison to predictions without fuzzy scoring and other related works, the stroke risk prediction using the proposed approach demonstrated higher accuracy, making it a promising method for early stroke detection and prevention.<\/jats:p>","DOI":"10.1145\/3703461","type":"journal-article","created":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T14:17:18Z","timestamp":1731075438000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Enhanced Fuzzy Score-Based Decision Support System for Early Stroke Prediction"],"prefix":"10.1145","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6711-9909","authenticated-orcid":false,"given":"Mayssa","family":"Ben Kahla","sequence":"first","affiliation":[{"name":"Higher Institute of Computer Science and Communication Techniques, University of Sousse, H. Sousse, Tunisia and RIADI Laboratory, National School of Computer Sciences, University of Manouba, Manouba, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1206-5675","authenticated-orcid":false,"given":"Dalel","family":"Kanzari","sequence":"additional","affiliation":[{"name":"Higher Institute of Applied Science and Technology, University of Sousse, Sousse, Tunisia and LARODEC, ISG Tunis, University of Tunis, Tunis, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9936-8531","authenticated-orcid":false,"given":"Sana","family":"Ben Amor","sequence":"additional","affiliation":[{"name":"University of Sousse, Sousse, Tunisia and Department of Neurology, Sousse, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9583-9797","authenticated-orcid":false,"given":"Sonia","family":"Ayachi Ghannouchi","sequence":"additional","affiliation":[{"name":"RIADI Laboratory, National School of Computer Sciences, University of Manouba, Manouba, Tunisia and Higher Institute of Management of Sousse, University of Sousse, Sousse, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1157-7510","authenticated-orcid":false,"given":"Ricardo","family":"Martinho","sequence":"additional","affiliation":[{"name":"School of Technology and Management, Polytechnic of Leiria, Leiria, Portugal and CINTESIS, University of Porto, Porto, Portugal"}]}],"member":"320","published-online":{"date-parts":[[2025,1,9]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2022.024492"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","unstructured":"Abdullah Albohari Abdul Kareem Alshami Abdul Nahas Adeel Aslam Mohammed Zawiah and Shazia Jamshed. 2020. 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