Cargando…
Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques
Applying data mining and machine learning (ML) techniques to clinical data might identify predictive biomarkers for diabetic nephropathy (DN), a common complication of type 2 diabetes mellitus (T2DM). A retrospective analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial wa...
Autores principales: | Rodriguez‐Romero, Violeta, Bergstrom, Richard F., Decker, Brian S., Lahu, Gezim, Vakilynejad, Majid, Bies, Robert R. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6742939/ https://www.ncbi.nlm.nih.gov/pubmed/31112000 http://dx.doi.org/10.1111/cts.12647 |
Ejemplares similares
-
Application of machine learning to predict reduction in total PANSS score and enrich enrollment in schizophrenia clinical trials
por: Podichetty, Jagdeep T., et al.
Publicado: (2021) -
Population pharmacokinetics, enzyme occupancy, and 24S‐hydroxycholesterol modeling of soticlestat, a novel cholesterol 24‐hydroxylase inhibitor, in healthy adults
por: Yin, Wei, et al.
Publicado: (2023) -
Model‐Based Approach to Predict Adherence to Protocol During Antiobesity Trials
por: Sharma, Vishnu D., et al.
Publicado: (2017) -
A case study of a patient‐centered reverse translational systems‐based approach to understand adverse event profiles in drug development
por: Kim, Sarah, et al.
Publicado: (2022) -
Application of a patient‐centered reverse translational systems‐based approach to understand mechanisms of an adverse drug reaction of immune checkpoint inhibitors
por: Kim, Sarah, et al.
Publicado: (2022)