评估皮肤癌治疗中AI决策支持的数据准备度，发现数据质量是关键瓶颈。
AI-Driven Decision Support in Oncology: Evaluating Data Readiness for Skin Cancer Treatment
- 通过文献、评估与专家研讨，系统分析数据可获取性与质量
- 识别出皮肤癌治疗关键数据点，但多数系统存在缺失或难提取
- 适合医疗数据治理与AI临床落地研究者参考
本研究聚焦于在慕尼黑大学医院皮肤肿瘤中心背景下，评估并提升人工智能（AI）驱动的临床决策支持系统（CDSS）在皮肤癌治疗中的数据准备度。研究采用多维度方法，包括文献回顾、数据准备度评估和专家工作坊，探讨将AI融入临床决策所面临的挑战。研究识别出皮肤癌治疗决策的关键数据要素，评估其在各类信息系统中的存在性与质量，并揭示从非结构化数据中提取信息的困难。结果表明，在复杂领域如肿瘤学中，高质量且可访问的数据是实现成功AI-CDSS的决定性因素。
原文摘要 · Abstract (English)
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 Münster, 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.
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