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Record Nr. |
UNINA9910483864603321 |
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Titolo |
Precision Health and Medicine : A Digital Revolution in Healthcare / / edited by Arash Shaban-Nejad, Martin Michalowski |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XIX, 197 p. 84 illus., 45 illus. in color.) |
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Collana |
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Studies in Computational Intelligence, , 1860-9503 ; ; 843 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Artificial intelligence |
Medical informatics |
Biomedical engineering |
Computational Intelligence |
Artificial Intelligence |
Health Informatics |
Biomedical Engineering and Bioengineering |
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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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Preface -- Chapter 1. From Precision Medicine to Precision Health: A Full Angle from Diagnosis to Treatment and Prevention -- Chapter 2. Constructing Accurate Confidence Intervals when Aggregating Social Media Data for Public Health Monitoring -- Chapter 3. MCA-based Rule Mining Enables Interpretable Inference in Clinical Psychiatry -- Chapter 4. Automatic Exercise Recognition with Machine Learning, etc. |
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Sommario/riassunto |
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This book highlights the latest advances in the application of artificial intelligence to healthcare and medicine. It gathers selected papers presented at the 2019 Health Intelligence workshop, which was jointly held with the Association for the Advancement of Artificial Intelligence (AAAI) annual conference, and presents an overview of the central issues, challenges, and potential opportunities in the field, along with new research results. By addressing a wide range of practical applications, the book makes the emerging topics of digital health and precision medicine accessible to a broad readership. Further, it offers |
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an essential source of information for scientists, researchers, students, industry professionals, national and international public health agencies, and NGOs interested in the theory and practice of digital and precision medicine and health, with an emphasis on risk factors in connection with disease prevention, diagnosis, and intervention. |
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