{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T23:13:49Z","timestamp":1771024429320,"version":"3.50.1"},"reference-count":62,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T00:00:00Z","timestamp":1699833600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004242","name":"Princess Nourah bint Abdulrahman University","doi-asserted-by":"publisher","award":["PNURSP2023R120"],"award-info":[{"award-number":["PNURSP2023R120"]}],"id":[{"id":"10.13039\/501100004242","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>The paper focuses on the hepatitis C virus (HCV) infection in Egypt, which has one of the highest rates of HCV in the world. The high prevalence is linked to several factors, including the use of injection drugs, poor sterilization practices in medical facilities, and low public awareness. This paper introduces a hyOPTGB model, which employs an optimized gradient boosting (GB) classifier to predict HCV disease in Egypt. The model\u2019s accuracy is enhanced by optimizing hyperparameters with the OPTUNA framework. Min-Max normalization is used as a preprocessing step for scaling the dataset values and using the forward selection (FS) wrapped method to identify essential features. The dataset used in the study contains 1385 instances and 29 features and is available at the UCI machine learning repository. The authors compare the performance of five machine learning models, including decision tree (DT), support vector machine (SVM), dummy classifier (DC), ridge classifier (RC), and bagging classifier (BC), with the hyOPTGB model. The system\u2019s efficacy is assessed using various metrics, including accuracy, recall, precision, and F1-score. The hyOPTGB model outperformed the other machine learning models, achieving a 95.3% accuracy rate. The authors also compared the hyOPTGB model against other models proposed by authors who used the same dataset.<\/jats:p>","DOI":"10.3390\/diagnostics13223439","type":"journal-article","created":{"date-parts":[[2023,11,14]],"date-time":"2023-11-14T02:20:37Z","timestamp":1699928437000},"page":"3439","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Optimizing HCV Disease Prediction in Egypt: The hyOPTGB Framework"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3048-1920","authenticated-orcid":false,"given":"Ahmed M.","family":"Elshewey","sequence":"first","affiliation":[{"name":"Computer Science Department, Faculty of Computers and Information, Suez University, Suez 43533, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3021-5902","authenticated-orcid":false,"given":"Mahmoud Y.","family":"Shams","sequence":"additional","affiliation":[{"name":"Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh 33516, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sayed M.","family":"Tawfeek","sequence":"additional","affiliation":[{"name":"Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amal H.","family":"Alharbi","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8352-6731","authenticated-orcid":false,"given":"Abdelhameed","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7080-1979","authenticated-orcid":false,"given":"Abdelaziz A.","family":"Abdelhamid","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, Egypt"},{"name":"Department of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra 11961, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marwa M.","family":"Eid","sequence":"additional","affiliation":[{"name":"Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt"},{"name":"Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura 35712, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8348-6530","authenticated-orcid":false,"given":"Nima","family":"Khodadadi","sequence":"additional","affiliation":[{"name":"Department of Civil and Architectural Engineering, University of Miami, Coral Gables, FL 33146, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2203-4549","authenticated-orcid":false,"given":"Laith","family":"Abualigah","sequence":"additional","affiliation":[{"name":"Computer Science Department, Prince Hussein Bin Abdullah Faculty for Information Technology, Al al-Bayt University, Mafraq 25113, Jordan"},{"name":"Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon"},{"name":"Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman 19328, Jordan"},{"name":"MEU Research Unit, Middle East University, Amman 11831, Jordan"},{"name":"Applied Science Research Center, Applied Science Private University, Amman 11931, Jordan"},{"name":"School of Computer Sciences, Universiti Sains Malaysia, Gelugor 11800, Malaysia"},{"name":"School of Engineering and Technology, Sunway University Malaysia, Petaling Jaya 27500, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9843-6392","authenticated-orcid":false,"given":"Doaa Sami","family":"Khafaga","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. 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