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Record Nr. |
UNINA9910554282103321 |
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Titolo |
Deep Learning for Personalized Healthcare Services / / ed. by Vishal Jain, Hadi Hedayati, Salahddine Krit, Omer Deperlioglu, Jyotir Moy Chatterjee |
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Pubbl/distr/stampa |
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Berlin ; ; Boston : , : De Gruyter, , [2021] |
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©2021 |
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ISBN |
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Descrizione fisica |
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1 online resource (XVIII, 250 p.) |
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Collana |
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Intelligent Biomedical Data Analysis , , 2629-7140 ; ; 7 |
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Soggetti |
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COMPUTERS / Social Aspects / General |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Frontmatter -- Preface -- Acknowledgments -- Contents -- Short Biography of Editors -- List of Contributors -- Deep learning for health and medicine -- Exploring Indian Yajna and mantra sciences for personalized health: pandemic threats and possible cures in twenty-first-century healthcare -- Advanced deep learning techniques and applications in healthcare services -- Visualizations of human bioelectricity with internal symptom captures: the Indo-Vedic concepts on Healthcare 4.0 -- Early cancer predictions using ensembles of machine learning and deep learning -- Deep learning in patient management and clinical decision making -- Patient health record system -- Prediction of multiclass cervical cancer using deep machine learning algorithms in healthcare services -- Comparative analysis for detecting skin cancer using SGD-based optimizer on a CNN versus DCNN architecture and ResNet-50 versus AlexNet on Adam optimizer -- Coronary heart disease analysis using two deep learning algorithms, CNN and RNN, and their sensitivity analyses -- An overview of the technological performance of deep learning in modern medicine -- Index |
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Sommario/riassunto |
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This book uncovers the stakes and possibilities involved in realising personalised healthcare services through efficient and effective deep |
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learning algorithms, enabling the healthcare industry to develop meaningful and cost-effective services. This requires effective understanding, application and amalgamation of deep learning with several other computing technologies, such as machine learning, data mining, and natural language processing. |
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