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  • Artificial Intelligence in Managing Antimicrobial Resistance

    Artificial Intelligence in Managing Antimicrobial Resistance by Pandey, Ramendra Pati; Chang, Chung-Ming; Raj, V. Samuel;

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      • Publisher's listprice GBP 130.00
      • 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.

        62 107 Ft (59 150 Ft + 5% VAT)
      • Discount 20% (cc. 12 421 Ft off)
      • Discounted price 49 686 Ft (47 320 Ft + 5% VAT)

    62 107 Ft

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    Availability

    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Edition number 1
    • Publisher CRC Press
    • Date of Publication 29 May 2025

    • ISBN 9781032812458
    • Binding Hardback
    • No. of pages170 pages
    • Size 216x138 mm
    • Weight 470 g
    • Language English
    • Illustrations 23 Illustrations, black & white; 3 Halftones, black & white; 20 Line drawings, black & white; 1 Tables, black & white
    • 666

    Categories

    Short description:

    The book is intended for academia, student of medical science, microbiology, biology, biotechnology. Furthermore, infectious diseases experts, scientists working in the field of infectious diseases, government health organizations, and medical.

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    Long description:

    This volume reviews the use of machine learning (ML) to predict antibiotic resistance in pathogens based on gene content and genome composition as data sets comprising hundreds or thousands of pathogen genomes become available. One of the main goals of this work is to promote the use of ML in front-line contexts while simultaneously emphasizing the additional improvements that are required to use these techniques in a secure and confident manner. Given the variety of quantitative and qualitative laboratory indicators of AMR, the issue of what to anticipate is not an easy one.


    This book is intended for academia, students of medical science, microbiology, biology, and biotechnology, as well as experts and scientists working in the fields of infectious diseases, government health organizations, and medicine.

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    Table of Contents:

    Preface. Role of Artificial Intelligence in Fighting Antimicrobial Resistance. Artificial Intelligence in Disease Surveillance and Monitoring Resistance Microbes. Artificial Intelligence in Antibiotic Discovery and Development. Artificial Intelligence for Precision Medicine in Antimicrobial Resistance. Artificial Intelligence-driven Diagnostics for Antimicrobial Resistance. Artificial Intelligence-Enabled Antimicrobial Stewardship Programs. Big Data Analytics and Antimicrobial Resistance. Artificial Intelligence in Veterinary Medicine and Antimicrobial Resistance. Ethical and Regulatory Considerations for Artificial Intelligence in Managing AMR. Index.

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