O-28 Artificial Intelligence in healthcare: ethical integration and impact on clinical practice

Methods: A mixed-methods descriptive study was conducted, integrating narrative literature review and a multicountry cross-sectional survey. PubMed and Scopus were searched for English language articles (2018–2024) using selected keywords as artificial intelligence in clinical decision support, artificial intelligence in education and artificial intelligence ethics. Articles were included based on relevance to clinical and ethical applications of artificial intelligence. Key findings from selected studies were reviewed, paraphrased, noted, and were used to support the manuscript. A structured, independent questionnaire was developed by the authors based on academic understanding of artificial intelligence in healthcare, without any predefined framework or existing validated questionnaire. The survey was administered via Google Forms among healthcare professionals and medical students across Guyana, India, Russia, and the Middle East. Informed consent was obtained. Descriptive statistical analysis was performed using frequencies and percentages.

Results: The literature consistently demonstrated that AI enhances diagnostic accuracy, improves workflow efficiency, and expands healthcare access. Among 200 respondents, 68% reported favorable perceptions and 65% reported active use of AI tools. While 70% followed AIgenerated recommendations, only 44% expressed high trust, highlighting a critical gap between utilization and confidence. Concerns regarding clinician replacement were limited (26%), while moderate comfort (52%) and perceived similarity to human reasoning (63%) indicated cautious acceptance. Ethical concerns including data privacy, bias, and lack of transparency were more pronounced in low-resource settings.

Conclusion: AI demonstrates measurable benefits in clinical efficiency and accessibility; however, the gap between