Busan Cancer Center, Biomedical Research Institute, Pusan National University Hospital, Busan, Korea.
Department of Internal Medicine, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea.
Indian J Cancer. 2023 Apr-Jun;60(2):211-216. doi: 10.4103/ijc.IJC_109_20.
Various clinical applications have been attempted using artificial intelligence (AI) clinical decision support system (CDSS), and it has become a starting point for personalized cancer treatment. We aimed to identify the degree of agreement between the AI-CDSS, Watson for Oncology (WFO), and the clinician in treatment recommendations for Korean breast cancer patients and to provide guidelines for future improvement.
One hundred and eighty-three breast cancer patients who underwent treatment at the Pusan National University Hospital between January 1, 2016 and May 31, 2017 were enrolled in this study. The concordance between WFO's and clinicians' treatment recommendations were examined according to various factors.
WFO gave the same treatment option recommendations as clinicians in 74 (40.4%) of the cases. According to the logistic regression, the difference in recommendation concordance between stage I and stage III was statistically significant (P = 0.004), and there was no difference among other factors.
The concordance of treatment recommendations was low overall. However, this is largely attributable to the differences of medical insurance system and healthcare environment between the United States and Korea. In the future, region-specific features should be considered or reflected during the development of AI-CDSS.
各种临床应用已经尝试使用人工智能（AI）临床决策支持系统（CDSS），它已成为个性化癌症治疗的起点。我们旨在确定 AI-CDSS、Watson for Oncology（WFO）与临床医生在韩国乳腺癌患者治疗建议中的一致性程度，并为未来的改进提供指导。
本研究纳入了 2016 年 1 月 1 日至 2017 年 5 月 31 日期间在釜山国立大学医院接受治疗的 183 名乳腺癌患者。根据各种因素，检查了 WFO 和临床医生治疗建议的一致性。
WFO 在 74 例（40.4%）中给出了与临床医生相同的治疗方案建议。根据逻辑回归，分期 I 和分期 III 之间的推荐一致性差异具有统计学意义（P=0.004），其他因素之间没有差异。
总体而言，治疗建议的一致性较低。然而，这主要归因于美国和韩国之间医疗保险制度和医疗保健环境的差异。未来，在开发 AI-CDSS 时，应考虑或反映特定地区的特点。
