Clinical use-cases and implementation guidelines for the development of valuable AI

Karina C. Borja Jiménez; Patrick Kemmeren; Marry van den Heuvel-Ebrink; Ronald de Krijger; Martha Grootenhuis; Marita Partanen; Norbert Graf; Shuping Wen; Alexander Leemans; Daniel L. Oberski; Reineke A. Schoot; Johannes H.M. Merks

doi:10.1016/j.ejcped.2024.100187

Clinical use-cases and implementation guidelines for the development of valuable AI

Karina C. Borja Jiménez, Patrick Kemmeren, Marry van den Heuvel-Ebrink, Ronald de Krijger, Martha Grootenhuis, Marita Partanen, Norbert Graf, Shuping Wen, Alexander Leemans, Daniel L. Oberski, Reineke A. Schoot^*, Johannes H.M. Merks

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

Contributing to UNICA4EU's vision to upscale and wide-scale the application of AI technology to pediatric cancer care, this paper provides guidelines for the development of an AI-based ecosystem and its potential implementation into clinical practice. We also provide clinical use cases (UC) that depict scenarios at different stages of the patient journey and showcase how data collected through different methods and techniques interact and could synergize with AI tools to improve diagnosis and risk stratification, facilitate clinical decision making, and help to adequately monitor patients’ quality of life (QoL). Pediatric oncologists and AI specialists crafted each UC considering current standards, unmet needs, and advancements in both precision medicine and AI to address identified challenges. UC depict transferable methods and processes applicable to other diseases, and show how different techniques could ideally converge at different stages, representing a use case on its own.

Original language	English
Article number	100187
Journal	EJC Paediatric Oncology
Volume	4
DOIs	https://doi.org/10.1016/j.ejcped.2024.100187
Publication status	Published - Dec 2024

Keywords

AI tools
Clinical use case
Genomics
MRI
Multimodal integration
Pediatric cancer
Quality of life

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10.1016/j.ejcped.2024.100187Licence: CC BY-NC-ND

1-s2.0-S2772610X24000473-mainFinal published version, 1 MBLicence: CC BY-NC-ND

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Borja Jiménez, K. C., Kemmeren, P., van den Heuvel-Ebrink, M., de Krijger, R., Grootenhuis, M., Partanen, M., Graf, N., Wen, S., Leemans, A., Oberski, D. L., Schoot, R. A., & Merks, J. H. M. (2024). Clinical use-cases and implementation guidelines for the development of valuable AI. EJC Paediatric Oncology, 4, Article 100187. https://doi.org/10.1016/j.ejcped.2024.100187

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keywords = "AI tools, Clinical use case, Genomics, MRI, Multimodal integration, Pediatric cancer, Quality of life",

author = "{Borja Jim{\'e}nez}, {Karina C.} and Patrick Kemmeren and {van den Heuvel-Ebrink}, Marry and {de Krijger}, Ronald and Martha Grootenhuis and Marita Partanen and Norbert Graf and Shuping Wen and Alexander Leemans and Oberski, {Daniel L.} and Schoot, {Reineke A.} and Merks, {Johannes H.M.}",

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year = "2024",

month = dec,

doi = "10.1016/j.ejcped.2024.100187",

language = "English",

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AU - Kemmeren, Patrick

AU - van den Heuvel-Ebrink, Marry

AU - de Krijger, Ronald

AU - Grootenhuis, Martha

AU - Partanen, Marita

AU - Graf, Norbert

AU - Wen, Shuping

AU - Leemans, Alexander

AU - Oberski, Daniel L.

AU - Schoot, Reineke A.

AU - Merks, Johannes H.M.

PY - 2024/12

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AB - Contributing to UNICA4EU's vision to upscale and wide-scale the application of AI technology to pediatric cancer care, this paper provides guidelines for the development of an AI-based ecosystem and its potential implementation into clinical practice. We also provide clinical use cases (UC) that depict scenarios at different stages of the patient journey and showcase how data collected through different methods and techniques interact and could synergize with AI tools to improve diagnosis and risk stratification, facilitate clinical decision making, and help to adequately monitor patients’ quality of life (QoL). Pediatric oncologists and AI specialists crafted each UC considering current standards, unmet needs, and advancements in both precision medicine and AI to address identified challenges. UC depict transferable methods and processes applicable to other diseases, and show how different techniques could ideally converge at different stages, representing a use case on its own.

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KW - Clinical use case

KW - Genomics

KW - MRI

KW - Multimodal integration

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KW - Quality of life

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Clinical use-cases and implementation guidelines for the development of valuable AI

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