Multimodal AI in Healthcare : A Paradigm Shift in Health Intelligence

Arash Shaban-Nejad

ISBN 10: 3031147707 / ISBN 13: 9783031147708

Published by Springer, Springer, 2022

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783031147708

Bibliographic Details

• Title: Multimodal AI in Healthcare : A Paradigm Shift in Health Intelligence
• Publisher: Springer, Springer
• Publication Date: 2022
• Language: English
• ISBN 10: 3031147707
• ISBN 13: 9783031147708
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 30D millimeters 241 millimeters width by 160 millimeters height by 30 millimeters depth
• Weight: 822 grams

About this title

Synopsis

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.