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A Review of the Use of Artificial Intelligence Algorithms for Predicting Injuries and Performance in Football Players
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The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury predictions, predicting injuries and analysing related risks, and evaluating player performance using AI models are the three main topics highlighted in the study. This study highlights the use of AI algorithms in the sports field to predict injuries and predict team or player performance, especially in football.

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Publication Date
Mon Oct 13 2025
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 17, Nº. 6, 2022, Págs. 405-407
Bullying behavior and its relationship to achievement motivation for young football players under (19) years old
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Autoría: Muwafaq Obayes Khudhair. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.

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Publication Date
Sun Sep 26 2021
Journal Name
Modern Sport
Effect of Rehabilitation Program by Using Hypermedia on Treatment Some of Shoulder Tissues Injuries for Badminton Players
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The important of present study is to design rehabilitation program by using hypermedia for some injuries of smooth tissues in shoulder joint.   This joint is most important to help badminton players in achieving their daily and sport tasks due to upper limp movements depend on health and active of this joint. Experimental approach with a manner of equal single station was used in present study and study simple consisted of 6 badminton players from Babylon and Al-Mahaweel clubs who have less sharp tissue smooth injury such (muscles, ligaments, pocket). We used (SPSS) to analyses pre, medal, post-tests data. In conclusion, hypermedia is positive benefit to rehabilitee of injuries of smooth tissues in shoulder joint for badminton pla

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Publication Date
Mon Oct 13 2025
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 17, Nº. 5, 2022, Págs. 275-278
The effect of therapeutic physical exercises in the rehabilitation of the knee joint injured partial rupture of the medial meniscal cartilage for football players
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Autorías: Ismael Saleem Abed, Imad Kadhim Khlaif, Salah Mahmood Salman. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 5, 2022. Artículo de Revista en Dialnet.

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Scopus
Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Literacy And Education
The availability of concepts and applications of artificial intelligence in the content of the chemistry textbook for the fourth scientific grade
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Publication Date
Mon Sep 09 2024
Journal Name
Научный Форум
the functioning of artificial intelligence for the development of communication skills among foreigners learning Russian
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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Intelligent Systems And Applications In Engineering
Artificial Intelligence Based Statistical Process Control for Monitoring and Quality Control of Water Resources: A Complete Digital Solution
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Scopus (4)
Scopus
Publication Date
Mon Oct 13 2025
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 17, Nº. 5, 2022, Págs. 269-271
The effect of a suggested rehabilitation curriculum in the treatment of partial rupture of the gluteal muscles and strengthening the working muscles of the pelvic joint in football players
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Autorías: Imad Kadhim Khlaif, Israa Gameel Hussein, Talib Faissal Shnawa. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 5, 2022. Artículo de Revista en Dialnet.

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Publication Date
Mon Oct 13 2025
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 17, Nº. 1, 2022, Págs. 33-35
The Effect of Using Therapeutic Physical Exercises Accompanying Physical Therapy in the Rehabilitation of Lumbar Disc Herniation for Football Players Aged (25-25)
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Autorías: Imad Kadhim Khlaif, Talib Faisal Shnawa. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 1, 2022. Artículo de Revista en Dialnet.

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Publication Date
Sun Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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Scopus (3)
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