Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging
Evaluation of tumor response to antivascular endothelial growth factor therapies in metastatic colorectal cancer (mCRC) is limited because morphological change in tumor may occur earlier or be more critical than tumor size change. Here, the authors present an analysis utilizing a deep learning netwo...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/05663aaff3704c2994241e2f448faf34 |
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| Sumario: | Evaluation of tumor response to antivascular endothelial growth factor therapies in metastatic colorectal cancer (mCRC) is limited because morphological change in tumor may occur earlier or be more critical than tumor size change. Here, the authors present an analysis utilizing a deep learning network to characterize tumor morphological change as well as tumor size changes for response assessment in mCRC patients. |
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