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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Title: Classification of painful or painless diabetic peripheral neuropathy and identification of the most powerful predictors using machine learning models in large cross-sectional cohorts.
Authors: Baskozos, Georgios1 (AUTHOR) georgios.baskozos@ndcn.ox.ac.uk, Themistocleous, Andreas C.1 (AUTHOR), Hebert, Harry L.2 (AUTHOR), Pascal, Mathilde M. V.1 (AUTHOR), John, Jishi1 (AUTHOR), Callaghan, Brian C.3 (AUTHOR), Laycock, Helen4 (AUTHOR), Granovsky, Yelena5 (AUTHOR), Crombez, Geert6 (AUTHOR), Yarnitsky, David5 (AUTHOR), Rice, Andrew S. C.4 (AUTHOR), Smith, Blair H.2 (AUTHOR), Bennett, David L. H.1 (AUTHOR)
Source: BMC Medical Informatics & Decision Making. Dec2022, Vol. 22 Issue 1, p1-23. 23p.
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  Data: 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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  Data: <searchLink fieldCode="JN" term="%22BMC+Medical+Informatics+%26+Decision+Making%22">BMC Medical Informatics & Decision Making</searchLink>. Dec2022, Vol. 22 Issue 1, p1-23. 23p.
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        Value: 10.1186/s12911-022-01890-x
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              Text: Dec2022
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