Accuracy of metabolomics profiles to non-invasively diagnose NAFLD stages and evolution by mean of machine-learning automated algorithms. (February 2020)

Record Type:
Journal Article
Title:
Accuracy of metabolomics profiles to non-invasively diagnose NAFLD stages and evolution by mean of machine-learning automated algorithms. (February 2020)
Main Title:
Accuracy of metabolomics profiles to non-invasively diagnose NAFLD stages and evolution by mean of machine-learning automated algorithms
Authors:
Masarone, M.
Troisi, J.
Aglitti, A.
Calvanese, G.
Torre, P.
Caruso, R.
Colucci, A.
Dallio, M.
Federico, A.
Balsano, C.
Persico, M.
Abstract:
Is Part Of:
Digestive and liver disease. Volume 52(2020)Supplement 1
Journal:
Digestive and liver disease
Issue:
Volume 52(2020)Supplement 1
Issue Display:
Volume 52, Issue 1 (2020)
Year:
2020
Volume:
52
Issue:
1
Issue Sort Value:
2020-0052-0001-0000
Page Start:
e9
Page End:
Publication Date:
2020-02
Subjects:
Digestive organs -- Diseases -- Periodicals
Liver -- Diseases -- Periodicals
616.33005
Journal URLs:
http://www.sciencedirect.com/science/journal/15908658 ↗
http://www.elsevier.com/journals ↗
DOI:
10.1016/j.dld.2019.12.023 ↗
Languages:
English
ISSNs:
1590-8658
Deposit Type:
Legaldeposit
View Content:
Available online (eLD content is only available in our Reading Rooms) ↗
Physical Locations:
British Library DSC - 3588.345600
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Ingest File:
21852.xml