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Contemporary healthcare heavily relies on advanced data analytics to enhance decision-making in cancer treatment (Arowoogun et al., 2024; Rehman et al., 2022; Smith et al., 2019; Zhai et al., 2023). However, the utilization of EMR data presents notable challenges, particularly regarding patient privacy within healthcare systems. It is imperative to assess the intricacies of cancer treatment on a global scale to identify underlying patterns that can enhance efficacy and reduce errors (Alowais et al., 2023; Venigandla, 2022; Ahmed et al., 2020Javaid et al., 2022; Lee et al., 2021). This study aims to leverage pattern algorithms and statistical methodologies to unearth insights that refine decision-making processes and elevate cancer therapy protocols (Yang et al., 2023; Naess & Haland, 2021; Durosini et al., 2021; Hoffman et al., 2021; Hong et al., 2020; Gupta & Patel, 2018). An in-depth examination of treatment patterns and health information systems provides valuable insights into the dynamics of cancer care, informing the development of tailored treatments within the Thai healthcare system (Sukasem et al., 2021; Pocock et al., 2020; Tansitpong et al., 2020; Suwannaprom et al, 2020; Jakovljevic et al., 2020; Tanaka et al., 2020). The development of drug treatment plans for cancer patients with concurrent medical conditions presents significant challenges (Johnson & White, 2019). This research underscores the intricate nature of healthcare providers' task in devising personalized treatment strategies for individuals with multiple medical conditions (Mohsin et al., 2023; Hamid et al., 2023; Rončević et al., 2023; Chen et al., 2022; Wang et al, 2021; Goutsouliak et al., 2020).