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...
Main Authors: | Baskozos, G, Themistocleous, A, Hebert, HL, Pascal, M, John, J, Bennett, D |
---|---|
Format: | Journal article |
Language: | English |
Published: |
BioMed Central
2022
|
Similar Items
-
Classification of painful or painless diabetic peripheral neuropathy and identification of the most powerful predictors using machine learning models in large cross-sectional cohorts
by: Georgios Baskozos, et al.
Published: (2022-05-01) -
Clinical advances in painful and painless diabetic neuropathy
by: YU Zhuoying, YANG Jing, JIANG Ye, LI Min
Published: (2023-06-01) -
Painful and painless channelopathies.
by: Bennett, D, et al.
Published: (2014) -
Painful and painless channelopathies
by: Bennett, D, et al.
Published: (2014) -
Vascular and nerve biomarkers in thigh skin biopsies differentiate painful from painless diabetic peripheral neuropathy
by: Gordon Sloan, et al.
Published: (2024-10-01)