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Combining CT Images and Clinical Features of Four Periods to Predict Whether Patients Have Rectal Cancer
In this paper, we mainly use random forest and broad learning system (BLS) to predict rectal cancer. A total of 246 participants with computed tomography (CT) image records were enrolled. The total model in the training set (combined with imaging and clinical indicators) has the best prediction resu...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670968/ https://www.ncbi.nlm.nih.gov/pubmed/34917137 http://dx.doi.org/10.1155/2021/4662061 |