Výsledky vyhledávání - "Ismaila Baldé"

Akademický článek

Differentiating Gliosarcoma from Glioblastoma: A Novel Approach Using PEACE and XGBoost to Deal with Datasets with Ultra-High Dimensional Confounders

Autor: Amir Saki, Usef Faghihi, Ismaila Baldé

Publikováno v: Life, Vol 14, Iss 7, p 882 (2024)

In this study, we used a recently developed causal methodology, called Probabilistic Easy Variational Causal Effect (PEACE), to distinguish gliosarcoma (GSM) from glioblastoma (GBM). Our approach uses a causal metric which combines Probabilistic Easy

Externí odkaz: https://doaj.org/article/15bf086ae22245739b2b184d4d3665b7

Zobrazit plný text záznamu

Plný text ve formátu HTML

Reader reaction to 'Outcome‐adaptive lasso: Variable selection for causal inference' by Shortreed and Ertefaie (2017)

Autor: Ismaila Baldé, Yi Archer Yang, Geneviève Lefebvre

Publikováno v: Biometrics. 79:514-520

Shortreed and Ertefaie introduced a clever propensity score variable selection approach for estimating average causal effects, namely, the outcome adaptive lasso (OAL). OAL aims to select desirable covariates, confounders, and predictors of outcome,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68dbd9b6ad52e2fc43d7edf6bafb5f30
https://doi.org/10.1111/biom.13683

Zobrazit plný text záznamu

Bayesian non-crossing quantile regression for regularly varying distributions

Autor: Ismaila Baldé, Salaheddine El Adlouni

Publikováno v: Journal of Statistical Computation and Simulation. 89:884-898

Quantile regression is a very important statistical tool for predictive modelling and risk assessment. For many applications, conditional quantile at different levels are estimated separately. Cons...

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4495d07d8d418791ca4114ccc28831ac
https://doi.org/10.1080/00949655.2019.1573899

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání