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XLVII Mexican Conference on Biomedical Engineering: Proceedings of CNIB 2024, November 79, 2024, Hermosillo, Sonora, México - Volume 1: Signal Processing And Bioinformatics [Mīkstie vāki]

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  • Formāts: Paperback / softback, 473 pages, height x width: 235x155 mm, XVIII, 473 p., 1 Paperback / softback
  • Sērija : IFMBE Proceedings 116
  • Izdošanas datums: 04-Jan-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 303182122X
  • ISBN-13: 9783031821226
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  • Mīkstie vāki
  • Cena: 162,93 €*
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  • Standarta cena: 191,69 €
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XLVII Mexican Conference on Biomedical Engineering: Proceedings of CNIB 2024, November 79, 2024, Hermosillo, Sonora, México - Volume 1: Signal Processing And BioinformaticsPalielināt
  • Formāts: Paperback / softback, 473 pages, height x width: 235x155 mm, XVIII, 473 p., 1 Paperback / softback
  • Sērija : IFMBE Proceedings 116
  • Izdošanas datums: 04-Jan-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 303182122X
  • ISBN-13: 9783031821226
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031821226.html
Keywords:
This book reports on cutting-edge research and best practices in the broad field of biomedical engineering. Based on the  XLVII Mexican Conference on Biomedical Engineering, CNIB 2024, held on November 7-9, 2024 in Hermosillo, Sonora, México, this first volume of the proceedings covers research topics in biomedical signal processing, computational biology and prosthetics, with applications of artificial intelligence for medical diagnosis, behavioral studies and more. All in all, this book provides a timely snapshot on state-of-the-art achievements in biomedical engineering and current challenges in the field. It addresses both researchers and professionals, and it is expected to foster future collaborations between the two groups, as well as international collaborations.

ML Design in Handwriting Analysis for Prediction of Alzheimer's Disease.- Machine learning for classification of electrooculography signals in the detection of visual fatigue syndrome.- Machine Learning Techniques for Classifying Cardiac Arrhythmias.- A Machine Learning approach to breast cancer detection in mammograms.