This research focuses on evaluating and enhancing data readiness for the development of an Artificial Intelligence (AI)-based Clinical Decision Support System (CDSS) in the context of skin cancer treatment. The study, conducted at the Skin Tumor Center of the University Hospital M\"unster, delves into the essential role of data quality, availability, and extractability in implementing effective AI applications in oncology. By employing a multifaceted methodology, including literature review, data readiness assessment, and expert workshops, the study addresses the challenges of integrating AI into clinical decision-making. The research identifies crucial data points for skin cancer treatment decisions, evaluates their presence and quality in various information systems, and highlights the difficulties in extracting information from unstructured data. The findings underline the significance of high-quality, accessible data for the success of AI-driven CDSS in medical settings, particularly in the complex field of oncology.

本研究聚焦于评估和提升用于人工智能临床决策支持系统（CDSS）的数据准备情况，特别是针对皮肤癌治疗。通过多方面的方法论，本研究识别了皮肤癌治疗决策的关键数据点，评估了这些数据在多种信息系统中的存在情况和质量，强调了高质量和可获取数据在人工智能驱动的CDSS成功应用中的重要性。

人工智能驱动的肿瘤决策支持：评估皮肤癌治疗的数据准备情况