Evaluation of Healthcare Professionals' Satisfaction with the Use of AI in Supporting Clinical Diagnosis

Abstract

The integration of artificial intelligence in clinical diagnosis promises improved efficiency and accuracy, but healthcare professionals' acceptance and satisfaction with this technology remain concerns. This study assessed the satisfaction levels of healthcare professionals utilising AI in clinical diagnosis, with a focus on the factors that influence their attitudes toward AI tools. A mixed-methods approach was employed, combining quantitative and qualitative methods. Quantitative data were collected through surveys that measured satisfaction and explored perceptions, experiences, and concerns regarding the use of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$A I$</tex> in clinical diagnosis. Quantitative analysis used descriptive and inferential statistics, and qualitative data were analysed through thematic analysis. Results indicated that satisfaction levels with AI varied based on factors such as transparency, reliability, and ethical considerations. Main concerns included a lack of understanding of AI algorithms, potential bias in decision-making, and legal liability implications. Conversely, professionals with positive AI experiences viewed it as a tool to reduce workload and enhance efficiency. This discussion highlights the importance of developing a comprehensive strategy to improve awareness, offer targeted training, establish clear ethical guidelines, and promote collaboration between AI developers and healthcare professionals. The study concludes that successful AI integration in clinical diagnosis requires attention to psychological, social, and ethical factors. By addressing barriers and maximising the potential of AI, the healthcare community can create a more efficient, empathetic, and equitable system.

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