Abstract
Artificial intelligence integration into healthcare has gained significant attention in recent years, with its use ranging from disease diagnosis to surgical assistance. While artificial intelligence's potential to improve patient outcomes and optimise patient care is undeniable, concerns regarding privacy, transparency, and the potential for medical errors persist. To take full advantage of artificial intelligence's transformative abilities, understanding patient perceptions and attitudes towards its integration into medicine is crucial for ethical considerations and health outcomes. This study aimed to describe patients' perceptions of medical artificial intelligence and its integration into the healthcare system, drawing attention to a crucial yet understudied aspect of artificial intelligence adoption in Kazakhstan. Descriptive qualitative design. From February to March 2024, the researchers conducted semi-structured interviews amongst 13 patients. The interviews were audio-recorded, transcribed, translated, and then analysed using a thematic analysis approach. The study adhered to the COREQ guidelines. Five themes emerged from 13 interviews: the benefits of artificial intelligence on patient care, the importance of human factors on patient care over artificial intelligence, revolutionising patient care delivery through artificial intelligence, patient education and artificial intelligence, and balancing technology and human interaction in artificial intelligence-driven intervention. Patient perceptions of artificial intelligence integration into healthcare were primarily positive. Nevertheless, patients prefer artificial intelligence as a supplementary tool under human supervision due to risks such as possible medical errors and violations of patient privacy. Patients provided the data for this study. The researchers interviewed them about their perceptions of medical artificial intelligence and its integration into the healthcare system. The patients or the public contributed nothing to the other aspects of the study.
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