Multimodal Ai in Healthcare : A Paradigm Shift in Health Intelligence. Dieser Artikel ist nicht verfügbar.
Sprache: Englisch
Verlag: Springer, 2022
Serie: Buch 534 von 538 - Studies in Computational Intelligence
- Hardcover
- Neu

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- Titel
- Multimodal Ai in Healthcare : A Paradigm Shift in Health Intelligence
- Autor
- Shaban-nejad, Arash (EDT); Michalowski, Martin (EDT); Bianco, Simone (EDT)
- Verlag
- Springer
- Erscheinungsjahr
- 2022
- Zustand
- New
- Einband
- Hardcover
- Sprache
- Englisch
- ISBN-10
- 3031147707
- ISBN-13
- 9783031147708
- Serie
- Buch 534 von 538: Studies in Computational Intelligence
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 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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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 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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