Literature DB >> 32558657

Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians.

Onur Asan1, Alparslan Emrah Bayrak1, Avishek Choudhury1.   

Abstract

Artificial intelligence (AI) can transform health care practices with its increasing ability to translate the uncertainty and complexity in data into actionable-though imperfect-clinical decisions or suggestions. In the evolving relationship between humans and AI, trust is the one mechanism that shapes clinicians' use and adoption of AI. Trust is a psychological mechanism to deal with the uncertainty between what is known and unknown. Several research studies have highlighted the need for improving AI-based systems and enhancing their capabilities to help clinicians. However, assessing the magnitude and impact of human trust on AI technology demands substantial attention. Will a clinician trust an AI-based system? What are the factors that influence human trust in AI? Can trust in AI be optimized to improve decision-making processes? In this paper, we focus on clinicians as the primary users of AI systems in health care and present factors shaping trust between clinicians and AI. We highlight critical challenges related to trust that should be considered during the development of any AI system for clinical use. ©Onur Asan, Alparslan Emrah Bayrak, Avishek Choudhury. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 19.06.2020.

Entities:  

Keywords:  FDA policy; bias; health care; human-AI collaboration; technology adoption; trust

Year:  2020        PMID: 32558657     DOI: 10.2196/15154

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   5.428


  43 in total

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Journal:  J Am Med Inform Assoc       Date:  2021-07-30       Impact factor: 4.497

Review 7.  Applications of interpretability in deep learning models for ophthalmology.

Authors:  Adam M Hanif; Sara Beqiri; Pearse A Keane; J Peter Campbell
Journal:  Curr Opin Ophthalmol       Date:  2021-09-01       Impact factor: 4.299

8.  Preliminary study of AI-assisted diagnosis using FDG-PET/CT for axillary lymph node metastasis in patients with breast cancer.

Authors:  Zongyao Li; Kazuhiro Kitajima; Kenji Hirata; Ren Togo; Junki Takenaka; Yasuo Miyoshi; Kohsuke Kudo; Takahiro Ogawa; Miki Haseyama
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Review 9.  Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review.

Authors:  Onur Asan; Avishek Choudhury
Journal:  JMIR Hum Factors       Date:  2021-06-18

Review 10.  Artificial intelligence extension of the OSCAR-IB criteria.

Authors:  Axel Petzold; Philipp Albrecht; Laura Balcer; Erik Bekkers; Alexander U Brandt; Peter A Calabresi; Orla Galvin Deborah; Jennifer S Graves; Ari Green; Pearse A Keane; Jenny A Nij Bijvank; Josemir W Sander; Friedemann Paul; Shiv Saidha; Pablo Villoslada; Siegfried K Wagner; E Ann Yeh
Journal:  Ann Clin Transl Neurol       Date:  2021-05-19       Impact factor: 4.511

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