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Vol-3068
urn:nbn:de:0074-3068-5
Copyright © 2021 for
the individual papers by the papers' authors.
Copyright © 2021 for the volume
as a collection by its editors.
This volume and its papers are published under the
Creative Commons License Attribution 4.0 International
(CC BY 4.0).
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AAAI-HUMAN 2021
Human Partnership with Medical AI: Design, Operationalization, and Ethics
Proceedings of the AAAI 2021 Fall Symposium on Human Partnership with Medical AI: Design, Operationalization, and Ethics (AAAI-HUMAN 2021)
Virtual Event, November 4-6, 2021.
Edited by
*
McMaster University,
Department of Electrical and Computer Engineering, Hamilton, Ontario, Canada
**
Virginia Tech,
Department of Computer Science, Blacksburg, Virginia, USA
***
Ryerson University,
Department of Electrical and Computer Engineering, Toronto, Ontario, Canada
*+
Mayo Clinic,
Division of Health Care Delivery Research, Scottsdale, Arizona, USA
*++
Virginia Tech,
Health Innovation and Implementation Science, Blacksburg, Virginia, USA
*-
Cornell University,
Bowers College of Computing and Information Science, Ithaca, New York, USA
*--
University of Edinburgh,
Behavioural Sciences and Clinical Surgery, Edinburgh, Scotland, United Kingdom
†
Vector Institute for Artificial Intelligence,
Toronto, Ontario, Canada
Table of Contents
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Preface
Thomas E. Doyle,
Reza Samavi,
Aisling Kelliher
Session: Short Papers
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Are Clinical BERT Models Privacy Preserving? The Difficulty of Extracting Patient-Condition Associations
Thomas Vakili,
Hercules Dalianis
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Multimodal Explanations for User-centric Medical Decision Support Systems
Bettina Finzel,
David Elias Tafler,
Anna Magdalena Thaler,
Ute Schmid
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PseudoNAM: A Pseudo Value Based Interpretable Neural Additive Model for Survival Analysis
Md Mahmudur Rahman,
Sanjay Purushotham
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Collaborative Human-ML Decision Making Using Experts’ Privileged Information Under Uncertainty
Mansoureh Maadi,
Hadi Akbarzadeh Khorshidi,
Uwe Aickelin
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Technical Feasibility, Financial Viability, and Clinician Acceptance: On the Many Challenges to AI in Clinical Practice
Nur Yildirim,
John Zimmerman,
Sarah Preum
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Automatic Medical Text Simplification: Challenges of Data Quality and Curation
Chandrayee Basu,
Rosni Vasu,
Michihiro Yasunaga,
Sohyeong Kim,
Qian Yang
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Grading OSPE Questions with Decision Learning Trees: A First Step Towards an Intelligent Tutoring System for Anatomical Education
Jason Bernard,
Bruce Wainman,
O’llenecia Walker,
Courtney Pitt,
Alex Bak,
Josh Mitchell,
Anthony Saraco,
Ilana Bayer,
Ranil Sonnadara
2021-12-22: submitted by Thomas Doyle, Yi Jui Lee,
metadata incl. bibliographic data published under Creative Commons CC0
2022-01-10: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073)
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