Investigating the paradoxes of doctors in Isfahan government hospitals in accepting artificial intelligence in healthcare environments
Code: G-1189
Authors: Maryam Azizinia * ℗
Schedule: Not Scheduled!
Tag: Health Policy, Law & Management in AI
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Abstract:
Abstract
The integration of AI and machine learning technologies into the medical field is a transformative force in improving healthcare, diagnostics, drug research, and healthcare, posing new challenges and increasing significantly. The aim of this article is to shed light on the paradoxes associated with the use of AI by healthcare workers and patients and to provide solutions to enable them to achieve the maximum benefits of this technology in healthcare settings. It was essential to understand how healthcare workers and patients accept AI in the treatment process. This study attempted to answer the question of whether advanced AI services are accepted in healthcare or not? Method: This review article systematically used various authoritative databases (Scopus, Web of Science, PubMed / EMBASE, Google Scholar) to retrieve relevant information and followed the PRISMA guidelines. Using a systematic search strategy and specific inclusion and exclusion criteria, 500 studies were found, of which only 54 were included after repeated exclusion and screening of articles. Results The findings of this study identified multiple benefits of using AI in healthcare, including its ability to improve diagnostic accuracy, improve treatment outcomes, and optimize healthcare delivery. However, ethical issues such as algorithmic bias, lack of transparency, data privacy issues for healthcare professionals and healthcare professionals, and the erosion of human values in patient care remain. Conclusion: The results showed that addressing these challenges in balancing technological innovation with human expertise to ensure responsible and ethically appropriate use and maximize the benefits of AI without causing serious drawbacks requires increasing awareness and infrastructure and optimizing for learning and accessibility. Ease of use, automation efficiency, diagnostic accuracy, and cost-effectiveness were identified as key factors driving the willingness to use and flexibility in adopting AI-based treatments, which were influenced by understanding the perspectives of healthcare providers and clients. It was suggested that policymakers develop clear, unique guidelines with a comprehensive approach and, with its support, review and mitigate the risks associated with artificial intelligence in the field of healthcare.
Keywords
Paradox, Artificial Intelligence, Healthcare
