AI Summary & Key Takeaways
AI InsightThese findings highlight the need for transparent, guideline-aligned AI systems and structured education for their integration into oncology practice.
📌 3 Key Takeaways
Abstract
Aims: Evidence-based guidelines standardize care; however, their expanding scope may hinder the consistent implementation of these guidelines. However, the impact of digital health and Artificial Intelligence (AI) on guideline adherence and clinician perspectives remains unclear. Methods: In this cross-sectional study, 94 medical oncologists completed a structured, Likert-scale questionnaire. Statistical analyses included Spearman’s correlation and Kruskal-Wallis tests were used to assess associations between variables, followed by multivariate linear regression to identify the independent predictors of AI perception. Results: Digital health technologies were frequently used (64.9%), and 76.6% of the participants reported that these tools accelerated the decision-making process. Of the participants, 31.9% indicated that decision-making would be more difficult without AI. Guideline adherence was notably high (94.7%), with over 75% supporting its role in personalized decision-making and integration of complex patient-specific factors, while 59.6% found it useful in data-limited clinical scenarios. The most commonly identified application areas were toxicity management (75.5%) and treatment selection (71.3%). Trust in AI was strongly associated with its alignment with established guidelines (91.5%), and most participants emphasized that AI should support clinical judgment within ethical and legal frameworks. In the multivariate analysis, future perspective emerged as the only independent predictor of AI perception (β=0.353). Conclusion: Medical oncologists demonstrated high guideline adherence and cautiously positive attitudes toward AI. Trust in AI is closely tied to guideline compatibility, and future expectations significantly shape AI acceptance. These findings highlight the need for transparent, guideline-aligned AI systems and structured education for their integration into oncology practice.