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

<strong>Background<br></strong> 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 mode...

Descrizione completa

Dettagli Bibliografici
Autori principali:	Baskozos, G, Themistocleous, A, Hebert, HL, Pascal, M, John, J, Bennett, D
Natura:	Journal article
Lingua:	English
Pubblicazione:	BioMed Central 2022

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

Documenti analoghi

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