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    <title>Artificial Intelligence in Sports, Movement, and Health</title>
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    <namePart>Dindorf, Carlo.</namePart>
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    <namePart>Gassmann, Freya.</namePart>
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    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
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    <extent>X, 270 p. 55 illus., 34 illus. in color. online resource.</extent>
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  <abstract>This comprehensive work explores Artificial Intelligence´s profound impact on revolutionizing how we approach sports, movement, and health. It presents a rich collection of insights, practical applications, and perspectives poised to transform these domains. Therefore, leading experts in the fields were brought together, offering diverse perspectives and applications across various disciplines. Through the examination of real-world use cases and future possibilities, this book empowers readers with knowledge, enhancing the understanding of the transformative potential of AI in sports, movement, and health.</abstract>
  <tableOfContents> -- Situating Sports Science in the Movement of Digitization.  -- AI in Sport Scientific Creation and Writing Process.  -- Advancing Endurance Sports with AI.  -- Sensors Internet of Things and Artificial Intelligence for the Diagnosis and Prevention.  -- Artificial Intelligence for Sport Injury Prediction.  -- Generative AI in Anti Doping Analysis in Sports.  -- A Brief Review of Artificial Intelligence for Sport Informatics.  -- Transferring Lessons Learned from Uncertainty.  -- Machine Learning in Biomechanics.  -- AI based Motion Capture.  -- Machine Learning in Tennis.  -- Using Convolutional Neural Network to Predict Sports.  -- Learning to Run Marathons.  -- Data driven Methods for Soccer Analysis.  -- Artificial Intelligence in Talent Identification and Development in Sport.</tableOfContents>
  <note type="statement of responsibility">edited by Carlo Dindorf, Eva Bartaguiz, Freya Gassmann, Michael Fröhlich.</note>
  <subject authority="lcsh">
    <topic>Medical sciences</topic>
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  <identifier type="isbn">9783031672569</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-3-031-67256-9</identifier>
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