# Development of deep neural network for individualized hepatobiliary toxicity prediction after liver <scp>SBRT</scp>

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/development-of-deep-neural-network-for-individualized-hepatobiliary-toxicity/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Bulat Ibragimov,Diego A.S. Toesca,Daniel T. Chang,Yixuan Yuan,Albert C. Koong,Lei Xing |
| Citations | 125 |
| DOI | 10.1002/mp.13122 |
| Fields | Medicine,Physics and Astronomy |
| Open Access | true |
| OA Status | green |
| OA URL | https://www.ncbi.nlm.nih.gov/pmc/articles/6192047 |
| OpenAlex ID | https://openalex.org/W2885185546 |
| PMID | 30098025 |
| Type | article |
| Year | 2018 |

## Paper authors

- [Bulat Ibragimov](https://scholariq.org/researchers/bulat-ibragimov/)

## Paper primary topic

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

## Paper topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Advanced Radiotherapy Techniques](https://scholariq.org/topics/advanced-radiotherapy-techniques/)
- [Effects of Radiation Exposure](https://scholariq.org/topics/effects-of-radiation-exposure/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.