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Record Nr. |
UNINA9910632485103321 |
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Titolo |
Multimodal AI in Healthcare : A Paradigm Shift in Health Intelligence / / edited by Arash Shaban-Nejad, Martin Michalowski, Simone Bianco |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (417 pages) : illustrations |
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Collana |
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Studies in Computational Intelligence, , 1860-9503 ; ; 1060 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Biomedical engineering |
Engineering - Data processing |
Artificial intelligence |
Computational Intelligence |
Biomedical Engineering and Bioengineering |
Data Engineering |
Artificial Intelligence |
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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 bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Unsupervised Numerical Reasoning to Extract Phenotypes from Clinical Text by Leveraging External Knowledge -- Customized Training of Pretrained Language Models to Detect Post Intents in Online Health Support Groups -- EXPECT-NLP: An Integrated Pipeline and User Interface for Exploring Patient Preferences Directly from Patient-Generated Text. |
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Sommario/riassunto |
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This book aims to highlight the latest achievements in the use of AI and multimodal artificial intelligence in biomedicine and healthcare. Multimodal AI is a relatively new concept in AI, in which different types of data (e.g. text, image, video, audio, and numerical data) are collected, integrated, and processed through a series of intelligence processing algorithms to improve performance. The edited volume contains selected papers presented at the 2022 Health Intelligence workshop and the associated Data Hackathon/Challenge, co-located with the Thirty-Sixth Association for the Advancement of Artificial |
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Intelligence (AAAI) conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. This book provides information for researchers, students, industry professionals, clinicians, and public health agencies interested in the applications of AI and Multimodal AI in public health and medicine. |
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