001453478 000__ 03659cam\a2200577\i\4500
001453478 001__ 1453478
001453478 003__ OCoLC
001453478 005__ 20230314003353.0
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001453478 008__ 221206s2023\\\\sz\a\\\\o\\\\\100\0\eng\d
001453478 019__ $$a1352795163$$a1352966746
001453478 020__ $$a9783031147715$$q(electronic bk.)
001453478 020__ $$a3031147715$$q(electronic bk.)
001453478 020__ $$z9783031147708
001453478 020__ $$z3031147707
001453478 0247_ $$a10.1007/978-3-031-14771-5$$2doi
001453478 035__ $$aSP(OCoLC)1353295616
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001453478 050_4 $$aR859.7.A78
001453478 08204 $$a610.285$$223/eng/20221206
001453478 1112_ $$aInternational Workshop on Health Intelligence$$d(2022)
001453478 24510 $$aMultimodal AI in healthcare :$$ba paradigm shift in health intelligence /$$cArash Shaban-Nejad, Martin Michalowski, Simone Bianco, editors.
001453478 264_1 $$aCham :$$bSpringer,$$c[2023]
001453478 264_4 $$c©2023
001453478 300__ $$a1 online resource (xxii, 416 pages) :$$billustrations (chiefly color).
001453478 336__ $$atext$$btxt$$2rdacontent
001453478 337__ $$acomputer$$bc$$2rdamedia
001453478 338__ $$aonline resource$$bcr$$2rdacarrier
001453478 4901_ $$aStudies in computational intelligence ;$$vvolume 1060
001453478 5050_ $$aUnsupervised Numerical Reasoning to Extract Phenotypes from Clinical Text by Leveraging External Knowledge -- Customized Training of Pretrained Language Models to Detect Post Intents in Online Health Support Groups -- EXPECT-NLP: An Integrated Pipeline and User Interface for Exploring Patient Preferences Directly from Patient-Generated Text.
001453478 506__ $$aAccess limited to authorized users.
001453478 520__ $$aThis book aims to highlight the latest achievements in the use of AI and multimodal artificial intelligence in biomedicine and healthcare. Multimodal AI is a relatively new concept in AI, in which different types of data (e.g. text, image, video, audio, and numerical data) are collected, integrated, and processed through a series of intelligence processing algorithms to improve performance. The edited volume contains selected papers presented at the 2022 Health Intelligence workshop and the associated Data Hackathon/Challenge, co-located with the Thirty-Sixth Association for the Advancement of Artificial Intelligence (AAAI) conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. This book provides information for researchers, students, industry professionals, clinicians, and public health agencies interested in the applications of AI and Multimodal AI in public health and medicine.
001453478 588__ $$aDescription based on print version record.
001453478 650_0 $$aArtificial intelligence$$xMedical applications$$vCongresses.
001453478 655_0 $$aElectronic books.
001453478 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001453478 655_7 $$aConference papers and proceedings.$$2lcgft
001453478 7001_ $$aShaban-Nejad, Arash,$$eeditor.$$1https://isni.org/isni/0000000495630311
001453478 7001_ $$aMichalowski, Martin,$$eeditor.
001453478 7001_ $$aBianco, Simone,$$eeditor.
001453478 7112_ $$aAAAI Conference on Artificial Intelligence$$n(36th :$$d2022)
001453478 77608 $$iPrint version:$$aInternational Workshop on Health Intelligence (2022), creator.$$tMultimodal AI in healthcare.$$dCham : Springer, 2022$$z9783031147708$$w(OCoLC)1346511421
001453478 830_0 $$aStudies in computational intelligence ;$$vv. 1060.
001453478 852__ $$bebk
001453478 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-14771-5$$zOnline Access$$91397441.1
001453478 909CO $$ooai:library.usi.edu:1453478$$pGLOBAL_SET
001453478 980__ $$aBIB
001453478 980__ $$aEBOOK
001453478 982__ $$aEbook
001453478 983__ $$aOnline
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