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- W4313308830 abstract "Artificial intelligence (AI) is being increasingly adopted in the health care industry for administrative tasks, patient care operations, and medical research.We aimed to examine health care workers' opinions about the adoption and implementation of AI-powered technology in the health care industry.Data were comments about AI posted on a web-based forum by 905 health care professionals from at least 77 countries, from May 2013 to October 2021. Structural topic modeling was used to identify the topics of discussion, and hierarchical clustering was performed to determine how these topics cluster into different groups.Overall, 12 topics were identified from the collected comments. These comments clustered into 2 groups: impact of AI on health care system and practice and AI as a tool for disease screening, diagnosis, and treatment. Topics associated with negative sentiments included concerns about AI replacing human workers, impact of AI on traditional medical diagnostic procedures (ie, patient history and physical examination), accuracy of the algorithm, and entry of IT companies into the health care industry. Concerns about the legal liability for using AI in treating patients were also discussed. Positive topics about AI included the opportunity offered by the technology for improving the accuracy of image-based diagnosis and for enhancing personalized medicine.The adoption and implementation of AI applications in the health care industry are eliciting both enthusiasm and concerns about patient care quality and the future of health care professions. The successful implementation of AI-powered technologies requires the involvement of all stakeholders, including patients, health care organization workers, health insurance companies, and government regulatory agencies." @default.
- W4313308830 created "2023-01-06" @default.
- W4313308830 creator A5069054032 @default.
- W4313308830 date "2023-01-27" @default.
- W4313308830 modified "2023-09-25" @default.
- W4313308830 title "Artificial Intelligence in Medicine: Text Mining of Health Care Workers’ Opinions" @default.
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- W4313308830 doi "https://doi.org/10.2196/41138" @default.
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