Imatinib adherence prediction using machine learning approach in patients with gastrointestinal stromal tumor

This study represents the first real-world investigation using ML techniques to predict risk factors associated with imatinib nonadherence in patients with GIST. By highlighting the potential factors and identifying high-risk patients, the multidisciplinary medical team can devise targeted strategies to effectively address the daily challenges of treatment adherence.