Machine-Learning Assisted Screening of Correlated Covariates: Application to Clinical Data of Desipramine.

Stepwise covariate modeling (SCM) has a high computational burden and can select the wrong covariates. Machine learning (ML) has been proposed as a screening tool to improve the efficiency of covariate selection, but little is known about how to apply ML on actual clinical data. First, we simulated datasets based on clinical data to compare the performance of various ML and traditional pharmacometrics (PMX) techniques with and without accounting for highly-correlated covariates.

Genetic factors associated with tuberculosis-related clinical outcomes in HIV-infected Black African patients: a systematic review and meta-analysis.

To evaluate the genetic factors influencing tuberculosis (TB) clinical outcomes in HIV-infected Black African patients. We systematically searched and identified eligible publications from >550 databases indexed through February 2021. Eighteen studies were included in the qualitative synthesis.

Publication proportions for registered breast cancer trials: before and following the introduction of the ClinicalTrials.gov results database.

Background: To limit selective and incomplete publication of the results of clinical trials, registries including ClinicalTrials.gov were introduced. The ClinicalTrials.