Data extraction and management are crucial components of research and clinical workflows in Radiation Oncology (RO), where accurate and comprehensive data are imperative to inform treatment planning and delivery. The advent of automated data mining scripts, particularly using the Python Environment for Scripting APIs (PyESAPI), has been a promising stride towards enhancing efficiency, accuracy, and reliability in extracting data from RO Information Systems (ROIS) and Treatment Planning Systems (TPS). This review dissects the role, efficiency, and challenges of implementing PyESAPI in RO data extraction and management, juxtaposing manual data extraction techniques and explicating future avenues

翻译：数据提取与管理是放射肿瘤学研究与临床工作流程中的关键环节，准确且全面的数据对于治疗规划与实施至关重要。基于Python脚本API环境（PyESAPI）的自动化数据挖掘脚本的出现，为提升从放射肿瘤学信息系统和放射治疗计划系统中提取数据的效率、准确性与可靠性提供了有力途径。本文综述了PyESAPI在放射肿瘤学数据提取与管理中的应用效能与实施挑战，通过对比手动数据提取技术，并展望了未来发展方向。