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  • XLVII Mexican Conference on Biomedical Engineering: Proceedings of CNIB 2024, November 7–9, 2024, Hermosillo, Sonora, México - Volume 1: Signal Processing And Bioinformatics

    XLVII Mexican Conference on Biomedical Engineering by Flores Cuautle, José de Jesús Agustín; Benítez-Mata, Balam; Reyes-Lagos, José Javier;

    Proceedings of CNIB 2024, November 7–9, 2024, Hermosillo, Sonora, México - Volume 1: Signal Processing And Bioinformatics

    Series: IFMBE Proceedings; 116;

      • GET 20% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 192.59
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        79 876 Ft (76 073 Ft + 5% VAT)
      • Discount 20% (cc. 15 975 Ft off)
      • Discounted price 63 901 Ft (60 858 Ft + 5% VAT)

    79 876 Ft

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    Long description:

    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.

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    Table of Contents:

    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.

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