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Titel:

A machine learning approach to risk assessment for alcohol withdrawal syndrome.

Dokumenttyp:
Journal Article; Research Support, Non-U.S. Gov't
Autor(en):
Burkhardt, Gerrit; Adorjan, Kristina; Kambeitz, Joseph; Kambeitz-Ilankovic, Lana; Falkai, Peter; Eyer, Florian; Koller, Gabi; Pogarell, Oliver; Koutsouleris, Nikolaos; Dwyer, Dominic B
Abstract:
At present, risk assessment for alcohol withdrawal syndrome relies on clinical judgment. Our aim was to develop accurate machine learning tools to predict alcohol withdrawal outcomes at the individual subject level using information easily attainable at patients' admission. An observational machine learning analysis using nested cross-validation and out-of-sample validation was applied to alcohol-dependent patients at two major detoxification wards (LMU, n = 389; TU, n = 805). 121 retrospective...     »
Zeitschriftentitel:
Eur Neuropsychopharmacol
Jahr:
2020
Band / Volume:
35
Seitenangaben Beitrag:
61-70
Volltext / DOI:
doi:10.1016/j.euroneuro.2020.03.016
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/32418843
Print-ISSN:
0924-977X
TUM Einrichtung:
2. Medizinische Klinik Toxikologische Abteilung (alt) (Prof. Zilker)
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