A promptable CT foundation model for solid tumor evaluation
Abstract Carcinogenesis is inherently complex, resulting in heterogeneous tumors with variable outcomes and frequent metastatic potential. Conventional longitudinal evaluation methods like RECIST 1.1 remain labor-intensive and prone to measurement errors, while existing AI solutions face critical li...
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| Main Authors: | Léo Machado, Léo Alberge, Hélène Philippe, Elodie Ferreres, Julien Khlaut, Julie Dupuis, Korentin Le Floch, Denis Habip Gatenyo, Pascal Roux, Jules Grégory, Maxime Ronot, Corentin Dancette, Tom Boeken, Daniel Tordjman, Pierre Manceron, Paul Hérent |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | npj Precision Oncology |
| Online Access: | https://doi.org/10.1038/s41698-025-00903-y |
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