Yichuan Wang

Yichuan Wang


Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2018 in Technological Forecasting and Social Change
Verified
Journal Article
Open access
YWYichuan Wang
Yichuan Wang
LKLeeAnn Kung
LeeAnn Kung
TBTerry Anthony Byrd
Terry Anthony Byrd

1 January 2021 in Journal of Business Research
Verified
Journal Article
Closed access
HLHuanli Li
Huanli Li
YWYun Wu
Yun Wu
DCDongmei Cao
Dongmei Cao
YWYichuan Wang
Yichuan Wang

1 January 2018 in Information & Management
Verified
Journal Article
Open access
YWYichuan Wang
Yichuan Wang
LKLeeAnn Kung
LeeAnn Kung
WWWilliam Yu Chung Wang
William Yu Chung Wang
CCCasey G. Cegielski
Casey G. Cegielski

1 January 2017 in Journal of Business Research
Verified
Journal Article
Open access
YWYichuan Wang
Yichuan Wang
NHNick Hajli
Nick Hajli

4 February 2022 in Social Science & Medicine
Verified
Journal Article
Open access
HSHaytham Siala
Haytham Siala
YWYichuan Wang
Yichuan Wang
A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare have emerged as AI becomes increasingly applicable and technologically advanced. The last decade has witnessed significant endeavors in striking a balance between ethical considerations and health transformation led by AI. Despite a growing interest in AI ethics, implementing AI-related technologies and initiatives responsibly in healthcare settings remains a challenge. In response to this topical challenge, we reviewed 253 articles pertaining to AI ethics in healthcare published between 2000 and 2020, summarizing the coherent themes of responsible AI initiatives. A preferred reporting items for systematic review and meta-analysis (PRISMA) approach was employed to screen and select articles, and a hermeneutic approach was adopted to conduct systematic literature review. By synthesizing relevant knowledge from AI governance and ethics, we propose a responsible AI initiative framework that encompasses five core themes for AI solution developers, healthcare professionals, and policy makers. These themes are summarized in the acronym SHIFT: Sustainability, Human centeredness, Inclusiveness, Fairness, and Transparency. In addition, we unravel the key issues and challenges concerning responsible AI use in healthcare, and outline avenues for future research.

1 December 2020 in Journal of Business Research
Verified
Journal Article
Open access
MTMina Tajvidi
Mina Tajvidi
MRMarie-Odile Richard
Marie-Odile Richard
YWYichuan Wang
Yichuan Wang
NHNick Hajli
Nick Hajli