{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:41:49Z","timestamp":1760150509743,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T00:00:00Z","timestamp":1700006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>In recent years the number of people who exercise every day has increased dramatically. More precisely, due to COVID period many people have become recreational runners. Recreational running is a regular way to keep active and healthy at any age. Additionally, running is a popular physical exercise that offers numerous health advantages. However, recreational runners report a high incidence of musculoskeletal injuries due to running. The healthcare industry has been compelled to use information technology due to the quick rate of growth and developments in electronic systems, the internet, and telecommunications. Our proposed intelligent system uses data mining algorithms for the rehabilitation guidance of recreational runners with musculoskeletal discomfort. The system classifies recreational runners based on a questionnaire that has been built according to the severity, irritability, nature, stage, and stability model and advise them on the appropriate treatment plan\/exercises to follow. Through rigorous testing across various case studies, our method has yielded highly promising results, underscoring its potential to significantly contribute to the well-being and rehabilitation of recreational runners facing musculoskeletal challenges.<\/jats:p>","DOI":"10.3390\/a16110523","type":"journal-article","created":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T10:57:46Z","timestamp":1700045866000},"page":"523","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Intelligent Injury Rehabilitation Guidance System for Recreational Runners Using Data Mining Algorithms"],"prefix":"10.3390","volume":"16","author":[{"given":"Theodoros","family":"Tzelepis","sequence":"first","affiliation":[{"name":"Department of Physical Education & Sports Sciences, Democritus University of Thrace, 69100 Komotini, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3461-0020","authenticated-orcid":false,"given":"George","family":"Matlis","sequence":"additional","affiliation":[{"name":"Department of Informatics, University of Western Macedonia, 52100 Kastoria, Greece"}]},{"given":"Nikos","family":"Dimokas","sequence":"additional","affiliation":[{"name":"Department of Informatics, University of Western Macedonia, 52100 Kastoria, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0483-4868","authenticated-orcid":false,"given":"Petros","family":"Karvelis","sequence":"additional","affiliation":[{"name":"Department of Informatics and Telecommunications, University of Ioannina, 47100 Arta, Greece"}]},{"given":"Paraskevi","family":"Malliou","sequence":"additional","affiliation":[{"name":"Department of Physical Education & Sports Sciences, Democritus University of Thrace, 69100 Komotini, Greece"}]},{"given":"Anastasia","family":"Beneka","sequence":"additional","affiliation":[{"name":"Department of Physical Education & Sports Sciences, Democritus University of Thrace, 69100 Komotini, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Scheerder, J., and Breedveld, K. 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