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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
Thu Sep 01 2016
Journal Name
Injury Prevention
972 The effectiveness of injury prevention program on reducing the incidence of lower limb injuries in adolescent male soccer players
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The highest incidence of injury is seen in adolescent playing pivoting sports such as soccer, basketball, and handball. Objective: To examine the effectiveness of a neuromuscular prevention program in reducing knee and ankle injuries in adolescent male soccer players.

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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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Scopus (72)
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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Development of human resources and their role in achieving artificial intelligence A survey of the views of a sample of workers in the cement plant
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The research topic was chosen as a result of the importance of human resource in business organizations in general and the industrial process in particular. Without the human resource, business organizations cannot continue and achieve success and excellence, and the research problem has been diagnosed in the lack of sales of General Cement Company’s northern products, despite their distinctiveness, standing, and reputation in The market and its products with standard specifications, and through this problem, the following questions were raised:                                                    &nbs

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Publication Date
Sun Jan 01 2023
Journal Name
Dental Hypotheses
Revolutionizing Systematic Reviews and Meta-analyses: The Role of Artificial Intelligence in Evidence Synthesis
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Scopus (26)
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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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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Diagnosis of Diabetes Using Artificial Intelligence Programs
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Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the

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Scopus (1)
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Publication Date
Mon Sep 28 2026
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 18, Nº. 1, 2023, Págs. 19-29
Constructing A Measure of Psychological Disability and Its Relationship to Some Basic Skills and Fixed Playing Situations for Youth Football Players Under (19) Years Old
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Autorías: Muwafaq Obayes Khudhair, Sanaa Rabeea Abed, Hayder Talib Jasim. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 1, 2023. Artículo de Revista en Dialnet.

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Publication Date
Sat May 18 2024
Journal Name
Proximus Journal Of Sports Science And Physical Education
STUDYING THE REALITY OF ADMINISTRATIVE PROBLEMS FOR MEMBERS OF THE ADMINISTRATIVE BODIES OF FIRST-CLASS FOOTBALL CLUBS FROM THE PLAYERS’ POINT OF VIEW
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The research aims to study the administrative problems in the sports management of the members of the administrative bodies of the first-class clubs of the province of Baghdad in football. The researchers used the descriptive approach (survey study) for its relevance to the nature of the research. The research community is represented by first-class football players, who numbered (176) players. The research sample was chosen by the deliberate method, as the basic research sample reached (136) individuals from the total research community. The researchers used the questionnaire to collect the necessary data to achieve the goal of the research by applying a questionnaire that aims to ident

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Publication Date
Sat Dec 01 2018
Journal Name
مجلة علوم التربية الرياضية
Identifying the standard levels of the most physical abilities and mobility of football players among ages (14-15) years
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Football is a game derived from the integration of football and tennis skills and some of the laws of volleyball and yard measurements, and since it is a newly created game must be studied and cover all aspects related to them to reach them to the highest levels. It is known that each game or sports activity should have Physical capabilities and motor skills, which is important to determine the level of technical performance where the abilities of the game contribute to mastering skills. The significance of the research in determining the standard levels of physical and motor abilities of the football players to help young professionals and the sponsors to increase the efficiency of these capabilities and thus raise the level of per

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Publication Date
Wed Dec 18 2024
Journal Name
Bmc Medical Education
Demographic factors, knowledge, attitude and perception and their association with nursing students’ intention to use artificial intelligence (AI): a multicentre survey across 10 Arab countries
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Scopus (49)
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