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Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT
BACKGROUND: Accurate prediction of radiation toxicity of healthy organs‐at‐risks (OARs) critically determines the radiation therapy (RT) success. The existing dose–volume histogram‐based metric may grossly under/overestimate the therapeutic toxicity after 27% in liver RT and 50% in head‐and‐neck RT....
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| Pubblicato in: | Med Phys |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
John Wiley and Sons Inc.
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6192047/ https://ncbi.nlm.nih.gov/pubmed/30098025 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/mp.13122 |
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