Implementation of AI in oncology: a systematic review of educational and clinical integration in global contexts

Abstract

Introduction: The global burden of cancer, coupled with inequalities in access to healthcare, has intensified interest in artificial intelligence (AI) as a transformative force in oncology. This study systematically analyzes how AI is being integrated into oncology education and clinical practice globally, highlighting its role in training the next generation of healthcare professionals. Methodology: A systematic review was conducted following the PRISMA and PICO guidelines, using data from PubMed, Scopus, and IEEE Xplore. Studies from 2019 to 2024 were selected based on empirical evaluations of AI-based educational interventions in oncology. Educational outcomes were extracted as performance (e.g., accuracy, test scores, comprehension/quality ratings), engagement/acceptability (e.g., usability or satisfaction ratings, completion), and skills development (e.g., task-based procedural metrics), as reported by each study. A total of 16 studies met the inclusion criteria after a rigorous selection and eligibility verification process. Results and discussion: The findings reveal that AI tools, especially chatbots based on large language models (e.g., ChatGPT), are increasingly being used in the education of both patients and professionals. Positive outcomes include improved knowledge retention, diagnostic reasoning, and engagement. Conclusion: AI is transforming cancer education through personalized and accessible learning experiences. Strategic integration, rigorous validation, and equitable access are essential for sustainable impact across diverse global settings.

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