Fathimal Mohamed (23 results)

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  • Language: English

    Published by Chapman and Hall/CRC, 2026

    1032527811 / 9781032527819

    • Softcover

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  • Language: English

    Published by Candh CRC Press, 2026

    1032527811 / 9781032527819

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    PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

  • Language: English

    Published by Candh CRC Press, 2026

    1032527811 / 9781032527819

    • Softcover

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    PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

  • Condition: New

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    Paperback. Condition: Brand New. 270 pages. 6.14x0.60x9.21 inches. In Stock.

  • Language: English

    Published by CRC Press, 2026

    1032527811 / 9781032527819

    • Softcover

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    Condition: New. P. Mohamed Fathimal is working as an Assistant Professor in the Department of Computer Science and Engineering, Anna University. She received her PhD, ME, and BE in Computer Science and Engineering from Manonmaniam Sundaranar University, Tirunelve.

  • Language: English

    Published by Chapman and Hall/CRC, 2025

    1032526106 / 9781032526102

    • Hardcover

    Seller: Books From California, Simi Valley, CA, U.S.A.Books From California

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    hardcover. Condition: Fine.

  • Language: English

    Published by Chapman and Hall/CRC, 2025

    1032526106 / 9781032526102

    • Hardcover

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    Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

  • Language: English

    Published by Taylor & Francis Ltd (Sales) Jun 2026, 2026

    1032527811 / 9781032527819

    • Softcover

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. Neuware - The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data. - Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health records - Covers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured data - Discusses supervised and unsupervised learning in electronic health records - Describes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health records This book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning. …

  • Language: English

    Published by Chapman and Hall/CRC, 2025

    1032526106 / 9781032526102

    • Hardcover

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    1032526106 / 9781032526102

    • Hardcover

    Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    1032526106 / 9781032526102

    • Hardcover

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    1032526106 / 9781032526102

    • Hardcover

    Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    1032526106 / 9781032526102

    • Hardcover

    Seller: California Books, Miami, FL, U.S.A.California Books

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    US$ 266.00

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    1032526106 / 9781032526102

    • Hardcover

    Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

  • Language: English

    Published by CRC Press, 2025

    1032526106 / 9781032526102

    • Hardcover

    Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    1032526106 / 9781032526102

    • Hardcover

    Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections

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    Condition: New. In English.

  • Language: English

    Published by Taylor and Francis Ltd, GB, 2025

    1032526106 / 9781032526102

    • Hardcover

    Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA

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    Hardback. Condition: New. The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data.Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health recordsCovers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured dataDiscusses supervised and unsupervised learning in electronic health recordsDescribes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health recordsThis book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning.…

  • Language: English

    Published by TAYLOR & FRANCIS NP EXCLUSIVE(CBS), 2025

    1032526106 / 9781032526102

    • Hardcover
    • International Edition

    Seller: UK BOOKS STORE, London, LONDO, United KingdomUK BOOKS STORE

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    Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

  • Condition: New

    US$ 372.95

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    Hardcover. Condition: Brand New. 304 pages. 9.18x6.12x9.21 inches. In Stock.

  • Language: English

    Published by Taylor and Francis Ltd, GB, 2025

    1032526106 / 9781032526102

    • Hardcover

    Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK

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    Hardback. Condition: New. The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data.Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health recordsCovers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured dataDiscusses supervised and unsupervised learning in electronic health recordsDescribes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health recordsThis book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning.…

  • Language: English

    Published by Taylor & Francis Ltd, 2026

    1032527811 / 9781032527819

    • Softcover
    • Print on Demand

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

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    Paperback. Condition: new. Paperback. The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data.Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health recordsCovers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured dataDiscusses supervised and unsupervised learning in electronic health recordsDescribes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health recordsThis book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning. The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR, consisting of demographics, medical history, and diagnosis. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

  • Language: English

    Published by Taylor & Francis Ltd, 2026

    1032527811 / 9781032527819

    • Softcover
    • Print on Demand

    Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    Paperback. Condition: new. Paperback. The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data.Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health recordsCovers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured dataDiscusses supervised and unsupervised learning in electronic health recordsDescribes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health recordsThis book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning. The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR, consisting of demographics, medical history, and diagnosis. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. …

  • Language: English

    Published by CRC Press, 2025

    1032526106 / 9781032526102

    • Hardcover
    • Print on Demand

    Seller: moluna, Greven, Germanymoluna

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. P. Mohamed Fathimal is working as an Assistant Professor in the Department of Computer Science and Engineering, Anna University. She received her PhD, ME, and BE in Computer Science and Engineering from Manonmaniam Sundaranar University, Tirunelve.…