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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...
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. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
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 |
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