Isbn: 9798184007830 - the hidden risks of ai in molecular diagnostics: why ai fails when stakes are high and how scientists catch the errors (3 risultati)

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  • Lingua: Inglese

    Editore: Independently Published Jul 2026, 2026

    9798184007830

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 14,72

    EUR 35,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Taschenbuch. Condizione: Neu. Neuware.

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798184007830

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    • Print on Demand

    Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

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    EUR 12,47

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    Spedito in U.S.A.

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    Paperback. Condizione: new. Paperback. The Hidden Risks of AI in Molecular DiagnosticsArtificial intelligence is rapidly transforming molecular biology and diagnostic laboratories, assisting with literature reviews, variant interpretation, primer design, protocol development, data analysis, and report generation. While these tools can significantly improve efficiency, they can also generate confident but incorrect answers that may go unnoticed in high-stakes clinical settings.In The Hidden Risks of AI in Molecular Diagnostics, Dr. Rajesh R. Kundapur examines where AI succeeds, where it fails, and why scientific validation remains essential when human health and clinical decisions are involved. Drawing on extensive experience in molecular diagnostics, genomics, and laboratory management, the author presents a practical framework for evaluating and validating AI-generated outputs using the principles of the scientific method.The book features 16 chapters which includes 21 real-world case studies demonstrating how AI can produce inaccurate interpretations, fabricated references, flawed experimental designs, incorrect calculations, misleading biological conclusions, and overconfident recommendations. Each case study illustrates how these errors can be detected, investigated, and corrected through systematic scientific validation.Readers will learn how to identify AI hallucinations, assess confidence, implement verification workflows, establish quality-control checkpoints, and safely integrate AI into laboratory operations without compromising scientific rigor.Whether you are a molecular biologist, clinical laboratory professional, bioinformatician, researcher, educator, student, or healthcare innovator, this book provides practical guidance for using AI responsibly in molecular diagnostics. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798184007830

    • Brossura
    • Print on Demand

    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    Condizione: Nuovo

    EUR 15,20

    EUR 43,72 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 1 disponibile

    Paperback. Condizione: new. Paperback. The Hidden Risks of AI in Molecular DiagnosticsArtificial intelligence is rapidly transforming molecular biology and diagnostic laboratories, assisting with literature reviews, variant interpretation, primer design, protocol development, data analysis, and report generation. While these tools can significantly improve efficiency, they can also generate confident but incorrect answers that may go unnoticed in high-stakes clinical settings.In The Hidden Risks of AI in Molecular Diagnostics, Dr. Rajesh R. Kundapur examines where AI succeeds, where it fails, and why scientific validation remains essential when human health and clinical decisions are involved. Drawing on extensive experience in molecular diagnostics, genomics, and laboratory management, the author presents a practical framework for evaluating and validating AI-generated outputs using the principles of the scientific method.The book features 16 chapters which includes 21 real-world case studies demonstrating how AI can produce inaccurate interpretations, fabricated references, flawed experimental designs, incorrect calculations, misleading biological conclusions, and overconfident recommendations. Each case study illustrates how these errors can be detected, investigated, and corrected through systematic scientific validation.Readers will learn how to identify AI hallucinations, assess confidence, implement verification workflows, establish quality-control checkpoints, and safely integrate AI into laboratory operations without compromising scientific rigor.Whether you are a molecular biologist, clinical laboratory professional, bioinformatician, researcher, educator, student, or healthcare innovator, this book provides practical guidance for using AI responsibly in molecular diagnostics. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…