AI-Driven Decision Support in Oncology: Evaluating Data Readiness for Skin Cancer Treatment
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866913732503797760 |
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| author | Grüger, Joscha Geyer, Tobias Brix, Tobias Storck, Michael Leson, Sonja Bley, Laura Weishaupt, Carsten Bergmann, Ralph Braun, Stephan A. |
| author_facet | Grüger, Joscha Geyer, Tobias Brix, Tobias Storck, Michael Leson, Sonja Bley, Laura Weishaupt, Carsten Bergmann, Ralph Braun, Stephan A. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_09164 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AI-Driven Decision Support in Oncology: Evaluating Data Readiness for Skin Cancer Treatment Grüger, Joscha Geyer, Tobias Brix, Tobias Storck, Michael Leson, Sonja Bley, Laura Weishaupt, Carsten Bergmann, Ralph Braun, Stephan A. Artificial Intelligence 68T99, 62P10, 92C50 I.2.6; J.3; H.2.8 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. |
| title | AI-Driven Decision Support in Oncology: Evaluating Data Readiness for Skin Cancer Treatment |
| topic | Artificial Intelligence 68T99, 62P10, 92C50 I.2.6; J.3; H.2.8 |
| url | https://arxiv.org/abs/2503.09164 |