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Evaluation von Entscheidungsbaummodellen des maschinellen Lernens für das akute Leberversagen nach Reanimation.
- Source :
- Anaesthesiologie & Intensivmedizin; Sep2022, Vol. 63 Issue 9, p350-361, 12p
- Publication Year :
- 2022
-
Abstract
- <i>Copyright of Anaesthesiologie & Intensivmedizin is the property of DGAI e.V. - Deutsche Gesellschaft fur Anasthesiologie und Intensivmedizin e.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
- Subjects :
- DISEASE risk factors
LIVER failure
CARDIOPULMONARY resuscitation
DECISION trees
MACHINE learning
RISK assessment
CARDIAC arrest
DESCRIPTIVE statistics
DECISION making in clinical medicine
SENSITIVITY & specificity (Statistics)
RECEIVER operating characteristic curves
ODDS ratio
ACUTE diseases
SECONDARY analysis
Subjects
Details
- Language :
- German
- ISSN :
- 01705334
- Volume :
- 63
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- Anaesthesiologie & Intensivmedizin
- Publication Type :
- Academic Journal
- Accession number :
- 159129381
- Full Text :
- https://doi.org/10.19224/ai2022.350