Additional file 3 of An 8-gene machine learning model improves clinical prediction of severe dengue progression

Autor: Liu, Yiran E., Saul, Sirle, Rao, Aditya Manohar, Robinson, Makeda Lucretia, Agudelo Rojas, Olga Lucia, Sanz, Ana Maria, Verghese, Michelle, Solis, Daniel, Sibai, Mamdouh, Huang, Chun Hong, Sahoo, Malaya Kumar, Gelvez, Rosa Margarita, Bueno, Nathalia, Estupiñan Cardenas, Maria Isabel, Villar Centeno, Luis Angel, Rojas Garrido, Elsa Marina, Rosso, Fernando, Donato, Michele, Pinsky, Benjamin A., Einav, Shirit, Khatri, Purvesh
Rok vydání: 2022
DOI: 10.6084/m9.figshare.19445704.v1
Popis: Additional file 3: Figure S1. Diagram of patients excluded from the independent Colombia cohort. Figure S2. Linear classifiers are age-dependent in public datasets. Figure S3. 8-gene XGBoost model predicts progression to SD in public datasets. Figure S4. Performance of two previously published gene signatures for predicting SD progression. Figure S5. 8-gene XGBoost model predictions improve precision and are generalizable by age and clinical classification in the Colombia cohort. Figure S6. Calibration of 8-gene XGBoost model to proportion of SD cases observed in the Colombia cohort. Figure S7. Model predictions are associated with some clinical features in the Colombia cohort. Figure S8. 8-gene signature may generalize to other viral infections.
Databáze: OpenAIRE