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Integrating multi-omics information in deep learning architectures for joint actuarial outcome prediction in non-small-cell lung cancer patients after radiation therapy
INTRODUCTION: Novel actuarial deep learning neural network (ADNN) architectures are proposed for joint prediction of radiotherapy outcomes, i.e., radiation pneumonitis (RP) and local control (LC) in stage III non-small-cell lung cancer (NSCLC) patients. Unlike NTCP/TCP models that use dosimetric inf...
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| Vydáno v: | Int J Radiat Oncol Biol Phys |
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| Hlavní autoři: | , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2021
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8180510/ https://ncbi.nlm.nih.gov/pubmed/33539966 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.ijrobp.2021.01.042 |
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