Mashayekhi Maryam, McBeth Rafe, Nguyen Dan, Yen Allen, Trivedi Zipalkumar, Moon Dominic, Avkshtol Vlad, Vo Dat, Sher David, Jiang Steve, Lin Mu-Han
Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA.
Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA.
Clin Transl Radiat Oncol. 2023 Mar 10;40:100616. doi: 10.1016/j.ctro.2023.100616. eCollection 2023 May.
•AI dose predictor was fully integrated with treatment planning system and used as a physicain decision support tool to improve uniformity of practice.•Model was trained based on our standard of practice, but implemented at the time of expansion with 3 new physicians join the practice.•Phase 1 retrospective evaluation demonstrated the non-uniform practice among 3 MDs and only 52.9% frequency planner can achieve physicians' directives.•Significant improvement in practice uniformity of practice was observed after utilizing AI as DST and 80.4% frequency clinical plan can achieve AI-guided physician directives.
•人工智能剂量预测器与治疗计划系统完全集成,并用作医生决策支持工具以提高实践的一致性。
•模型根据我们的实践标准进行训练,但在扩展时实施,当时有3名新医生加入该实践。
•第一阶段回顾性评估表明3名医生之间的实践不一致,只有52.9%的频率规划器能够达到医生的指令。
•在将人工智能用作决策支持工具后,观察到实践一致性有显著改善,80.4%的频率临床计划能够达到人工智能指导的医生指令。