Revolutionizing gastrointestinal cancer research with artificial intelligence: From precision patient stratification to real-world evidence.
Zhe Wang, Rui-Ying Zhang, Cheng Ji, Jia-Yi Zhang, Bing-Tong Yue, Feng Wang
Abstract
Open AccessGastrointestinal (GI) cancers exact a staggering global toll through high incidence, mortality, and treatment costs, yet clinical research continues to be hampered by inadequate patient stratification, challenging recruitment, suboptimal adherence, and time-consuming endpoint confirmations. Against this backdrop, artificial intelligence (AI) emerges as a powerful game-changer, offering streamlined trial design, predictive enrollment matching, dynamic endpoint assessment, and real-world data integration. This review synthesizes AI-driven advancements across the GI cancer research continuum. It covers precise patient stratification, automated efficacy evaluations, and remote compliance management. The analysis also addresses persistent challenges in data standardization, privacy protection, and regulatory oversight. We underscore the need for synergistic clinician-AI collaboration, alongside robust frameworks that ensure interpretability and ethical deployment. By illuminating the potential of AI to accelerate trial timelines, refine patient selection, and enhance outcome measurement, we aim to inspire new strategies that can significantly reduce the global burden of GI malignancies. Ultimately, this work provides a blueprint for stakeholders seeking to harness AI's transformative capabilities, fostering a future in which GI cancer clinical research becomes more agile, personalized, and impactful for patients and healthcare systems alike.