AI-Driven Decision Support in Oncology: Evaluating Data Readiness for Skin Cancer Treatment

• URL: http://arxiv.org/abs/2503.09164v1
• Date: Wed, 12 Mar 2025 08:49:03 GMT
• Title: AI-Driven Decision Support in Oncology: Evaluating Data Readiness for Skin Cancer Treatment
• Authors: Joscha Grüger, Tobias Geyer, Tobias Brix, Michael Storck, Sonja Leson, Laura Bley, Carsten Weishaupt, Ralph Bergmann, Stephan A. Braun,
• Abstract summary: 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.<n>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.
• Score: 0.1741346113266207
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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.

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