Classification of painful or painless diabetic peripheral neuropathy and identification of the most powerful predictors using machine learning models in large cross-sectional cohorts

BACKGROUND: To improve the treatment of painful Diabetic Peripheral Neuropathy (DPN) and associated co-morbidities, a better understanding of the pathophysiology and risk factors for painful DPN is required. Using harmonised cohorts (N = 1230) we have built models that classify painful versus painle...

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Detalles Bibliográficos
Autores principales: Baskozos, Georgios, Themistocleous, Andreas C., Hebert, Harry L., Pascal, Mathilde M. V., John, Jishi, Callaghan, Brian C., Laycock, Helen, Granovsky, Yelena, Crombez, Geert, Yarnitsky, David, Rice, Andrew S. C., Smith, Blair H., Bennett, David L. H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9150351/
https://www.ncbi.nlm.nih.gov/pubmed/35644620
http://dx.doi.org/10.1186/s12911-022-01890-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9150351/
https://www.ncbi.nlm.nih.gov/pubmed/35644620
http://dx.doi.org/10.1186/s12911-022-01890-x

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