ARS Conceptual Framework for AI-Driven Systematic Reviews in Sports Science and Medicine
Sports coaching and medical teams require valuable, accessible information to support their practices, and systematic reviews offer a well-established, trusted method of producing synthesised evidence to inform their decision-making. However, it entails significant costs due to the required time and...
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| Format: | Article |
| Language: | Catalan |
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Institut Nacional d´Educació Física de Catalunya (INEFC)
2025-07-01
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| Series: | Apunts: Educación Física y Deportes |
| Subjects: | |
| Online Access: | https://revista-apunts.com/ars-conceptual-framework-for-ai-driven-systematic-reviews-in-sports-science-and-medicine/ |
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| _version_ | 1849233929777709056 |
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| author | Tiago Fernandes Marta Castañer Oleguer Camerino |
| author_facet | Tiago Fernandes Marta Castañer Oleguer Camerino |
| author_sort | Tiago Fernandes |
| collection | DOAJ |
| description | Sports coaching and medical teams require valuable, accessible information to support their practices, and systematic reviews offer a well-established, trusted method of producing synthesised evidence to inform their decision-making. However, it entails significant costs due to the required time and human resources, while immediate and systematic evidence synthesis methods remain scarce. Despite the recent advances in machine learning and natural language processing in making information task automation viable, a notable gap seems to exist in their integration and within the principles of the scientific method. Therefore, this scientific note presents the structure and conceptualisation of a proposed framework to automate the workflow of systematic reviews, illustrated through an early implementation within a web application, namely Automatic Research Synthesis (ARS), intending to reduce the time and effort required by researchers and practitioners in sports science and medicine. |
| format | Article |
| id | doaj-art-cb980656249d40eb9b6aba0df52ca36c |
| institution | Kabale University |
| issn | 1577-4015 2014-0983 |
| language | Catalan |
| publishDate | 2025-07-01 |
| publisher | Institut Nacional d´Educació Física de Catalunya (INEFC) |
| record_format | Article |
| series | Apunts: Educación Física y Deportes |
| spelling | doaj-art-cb980656249d40eb9b6aba0df52ca36c2025-08-20T04:03:20ZcatInstitut Nacional d´Educació Física de Catalunya (INEFC)Apunts: Educación Física y Deportes1577-40152014-09832025-07-014136874https://doi.org/10.5672/apunts.2014-0983.es.(2025/3).161.08ARS Conceptual Framework for AI-Driven Systematic Reviews in Sports Science and MedicineTiago Fernandes0https://orcid.org/0000-0001-5714-410XMarta Castañer1https://orcid.org/0000-0001-7580-3068Oleguer Camerino2https://orcid.org/0000-0002-9069-6448National Institute of Physical Education of Catalonia (INEFC), University of Lleida (UdL), Lleida, SpainNational Institute of Physical Education of Catalonia (INEFC), University of Lleida (UdL), Lleida, SpainNational Institute of Physical Education of Catalonia (INEFC), University of Lleida (UdL), Lleida, SpainSports coaching and medical teams require valuable, accessible information to support their practices, and systematic reviews offer a well-established, trusted method of producing synthesised evidence to inform their decision-making. However, it entails significant costs due to the required time and human resources, while immediate and systematic evidence synthesis methods remain scarce. Despite the recent advances in machine learning and natural language processing in making information task automation viable, a notable gap seems to exist in their integration and within the principles of the scientific method. Therefore, this scientific note presents the structure and conceptualisation of a proposed framework to automate the workflow of systematic reviews, illustrated through an early implementation within a web application, namely Automatic Research Synthesis (ARS), intending to reduce the time and effort required by researchers and practitioners in sports science and medicine.https://revista-apunts.com/ars-conceptual-framework-for-ai-driven-systematic-reviews-in-sports-science-and-medicine/artificial intelligenceevidence-based practiceinformation systemsnatural language processingresearch synthesis |
| spellingShingle | Tiago Fernandes Marta Castañer Oleguer Camerino ARS Conceptual Framework for AI-Driven Systematic Reviews in Sports Science and Medicine Apunts: Educación Física y Deportes artificial intelligence evidence-based practice information systems natural language processing research synthesis |
| title | ARS Conceptual Framework for AI-Driven Systematic Reviews in Sports Science and Medicine |
| title_full | ARS Conceptual Framework for AI-Driven Systematic Reviews in Sports Science and Medicine |
| title_fullStr | ARS Conceptual Framework for AI-Driven Systematic Reviews in Sports Science and Medicine |
| title_full_unstemmed | ARS Conceptual Framework for AI-Driven Systematic Reviews in Sports Science and Medicine |
| title_short | ARS Conceptual Framework for AI-Driven Systematic Reviews in Sports Science and Medicine |
| title_sort | ars conceptual framework for ai driven systematic reviews in sports science and medicine |
| topic | artificial intelligence evidence-based practice information systems natural language processing research synthesis |
| url | https://revista-apunts.com/ars-conceptual-framework-for-ai-driven-systematic-reviews-in-sports-science-and-medicine/ |
| work_keys_str_mv | AT tiagofernandes arsconceptualframeworkforaidrivensystematicreviewsinsportsscienceandmedicine AT martacastaner arsconceptualframeworkforaidrivensystematicreviewsinsportsscienceandmedicine AT oleguercamerino arsconceptualframeworkforaidrivensystematicreviewsinsportsscienceandmedicine |