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

<h2>Abstract</h2> 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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Publication Details

Journal
EJC Paediatric Oncology
Published
2024-08-29
DOI
https://doi.org/10.1016/j.ejcped.2024.100187
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.12

Funders

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article

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

Johannes H. M. Merks, Reineke A. Schoot, Norbert M. Graf, Alexander Leemans et al.
1 citations
EJC Paediatric Oncology
Artificial Intelligence in Healthcare and Education
0.12
article

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

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

Abstract

<h2>Abstract</h2> 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.

EJC Paediatric OncologyVol. 4
Utrecht University (NL), University Medical Center Utrecht (NL), Princess Máxima Center (NL), Saarland University (DE)
European Commission
Openalex Percentile: Top 49%
Artificial Intelligence in Healthcare and Education
0.12
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