IoT, machine learning and data analytics for smart healthcare / edited by Mourade Azrour, Jamal Mabrouki, Azidine Guezzaz, Shakir Khan, and Said Benikrane.

Other author Azrour, Mourade.
Format Electronic
EditionFirst edition.
Publication InfoBoca Raton, FL : CRC Press, 2024.
Descriptionpages cm
Supplemental ContentFull text available from eBooks on EBSCOhost
Subjects

Partial contents Applications of blockchain in healthcare: review study / Souhayla Dargaoui, Mourade Azrour, Ahmad El Allauoi, Azidine Guezzaz, Said Benkirane, Jamal Mabrouki, Abdulatif Alabdulitif, Fatima Amounas -- Deep learning for healthcare management / Ankush Verma, Amit Pratap Singh Chouhan, Vandana Singh, Sanjana Koranga , Mourade Azrour -- Exploring lung cancer pathologies using metaphoric interventions of deep learning techniques / Swapnali Patil, Dr. Lakshmi D.
Abstract "Machine Learning, Internet of Things (IoT) and data analytics are new and fresh technologies that are being increasingly adopted in the field of medicine. This book positions itself at the forefront of this movement, exploring the beneficial applications of these new technologies and how they are gradually creating a smart healthcare system. This book details the various ways in which machine learning, data analytics and IoT solutions are instrumental in disease prediction in smart healthcare. For example, wearable sensors further help doctors and healthcare managers to monitor patients remotely and collect their health parameters in real-time, which can then be used to create datasets to develop machine learning models that can aid in the prediction and detection of any susceptible disease. In this way, smart healthcare can provide novel solutions to traditional medical issues. This book is a useful overview for scientists, researchers, practitioners and academics specialising in the field of intelligent healthcare, as well as containing additional appeal as a reference book for undergraduate and graduate students"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2023044532
ISBN9781032551074 (hbk)
ISBN9781032551098 (pbk)
ISBN(ebk)

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