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...

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Dades bibliogràfiques
Autors principals:	Baskozos, G, Themistocleous, A, Hebert, HL, Pascal, M, John, J, Bennett, D
Format:	Journal article
Idioma:	English
Publicat:	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​​​​​​​

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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