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Artificial intelligence support in MR imaging of incidental renal masses: an early health technology assessment

OBJECTIVE: This study analyzes the potential cost-effectiveness of integrating an artificial intelligence (AI)-assisted system into the differentiation of incidental renal lesions as benign or malignant on MR images during follow-up. - MATERIALS AND METHODS: For estimation of quality-adjusted life y...

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Main Authors: Marka, Alexander Wolfgang (Author) , Luitjens, Johanna (Author) , Gassert, Florian T. (Author) , Steinhelfer, Lisa (Author) , Burian, Egon (Author) , Rübenthaler, Johannes (Author) , Schwarze, Vincent (Author) , Froelich, Matthias F. (Author) , Makowski, Marcus R. (Author) , Gassert, Felix (Author)
Format: Article (Journal)
Language:English
Published: 23 February 2024
In: European radiology
Year: 2024, Volume: 34, Issue: 9, Pages: 5856-5865
ISSN:1432-1084
DOI:10.1007/s00330-024-10643-5
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1007/s00330-024-10643-5
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Author Notes:Alexander W. Marka, Johanna Luitjens, Florian T. Gassert, Lisa Steinhelfer, Egon Burian, Johannes Rübenthaler, Vincent Schwarze, Matthias F. Froelich, Marcus R. Makowski and Felix G. Gassert
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Summary:OBJECTIVE: This study analyzes the potential cost-effectiveness of integrating an artificial intelligence (AI)-assisted system into the differentiation of incidental renal lesions as benign or malignant on MR images during follow-up. - MATERIALS AND METHODS: For estimation of quality-adjusted life years (QALYs) and lifetime costs, a decision model was created, including the MRI strategy and MRI + AI strategy. Model input parameters were derived from recent literature. Willingness to pay (WTP) was set to $100,000/QALY. Costs of
Item Description:Gesehen am 26.07.2024
Physical Description:Online Resource
ISSN:1432-1084
DOI:10.1007/s00330-024-10643-5

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