Risk of AI in Healthcare: A Comprehensive Literature Review and Study
Framework
- URL: http://arxiv.org/abs/2309.14530v1
- Date: Mon, 25 Sep 2023 21:09:21 GMT
- Title: Risk of AI in Healthcare: A Comprehensive Literature Review and Study
Framework
- Authors: Apoorva Muley, Prathamesh Muzumdar, George Kurian, and Ganga Prasad
Basyal
- Abstract summary: This study conducts a thorough examination of the research stream focusing on AI risks in healthcare, aiming to explore the distinct genres within this domain.
A selection criterion was employed to carefully analyze 39 articles to identify three primary genres of AI risks prevalent in healthcare: clinical data risks, technical risks, and socio-ethical risks.
- Score: 0.5130062125323206
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This study conducts a thorough examination of the research stream focusing on
AI risks in healthcare, aiming to explore the distinct genres within this
domain. A selection criterion was employed to carefully analyze 39 articles to
identify three primary genres of AI risks prevalent in healthcare: clinical
data risks, technical risks, and socio-ethical risks. Selection criteria was
based on journal ranking and impact factor. The research seeks to provide a
valuable resource for future healthcare researchers, furnishing them with a
comprehensive understanding of the complex challenges posed by AI
implementation in healthcare settings. By categorizing and elucidating these
genres, the study aims to facilitate the development of empirical qualitative
and quantitative research, fostering evidence-based approaches to address
AI-related risks in healthcare effectively. This endeavor contributes to
building a robust knowledge base that can inform the formulation of risk
mitigation strategies, ensuring safe and efficient integration of AI
technologies in healthcare practices. Thus, it is important to study AI risks
in healthcare to build better and efficient AI systems and mitigate risks.
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