Artikel ; Online: Deep Learning Algorithm-Based Magnetic Resonance Imaging Feature-Guided Serum Bile Acid Profile and Perinatal Outcomes in Intrahepatic Cholestasis of Pregnancy.
Computational and mathematical methods in medicine
2022 Band 2022, Seite(n) 8081673
Abstract: This study was aimed to explore magnetic resonance imaging (MRI) based on deep learning belief network model in evaluating serum bile acid profile and adverse perinatal outcomes of intrahepatic cholestasis of pregnancy (ICP) patients. Fifty ICP pregnant ... ...
Abstract | This study was aimed to explore magnetic resonance imaging (MRI) based on deep learning belief network model in evaluating serum bile acid profile and adverse perinatal outcomes of intrahepatic cholestasis of pregnancy (ICP) patients. Fifty ICP pregnant women diagnosed in hospital were selected as the experimental group, 50 healthy pregnant women as the blank group, and 50 patients with cholelithiasis as the gallstone group. Deep learning belief network (DLBN) was built by stacking multiple restricted Boltzmann machines, which was compared with the recognition rate of convolutional neural network (CNN) and support vector machine (SVM), to determine the error rate of different recognition methods on the test set. It was found that the error rate of deep learning belief network (7.68%) was substantially lower than that of CNN (21.34%) and SVM (22.41%) ( |
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Mesh-Begriff(e) | Bile Acids and Salts ; Cholestasis, Intrahepatic ; Deep Learning ; Female ; Gallstones ; Glycocholic Acid ; Humans ; Magnetic Resonance Imaging ; Pregnancy ; Pregnancy Complications ; Pregnancy Outcome |
Chemische Substanzen | Bile Acids and Salts ; Glycocholic Acid (G59NX3I3RT) |
Sprache | Englisch |
Erscheinungsdatum | 2022-06-06 |
Erscheinungsland | United States |
Dokumenttyp | Journal Article |
ZDB-ID | 2252430-7 |
ISSN | 1748-6718 ; 1748-670X ; 1027-3662 |
ISSN (online) | 1748-6718 |
ISSN | 1748-670X ; 1027-3662 |
DOI | 10.1155/2022/8081673 |
Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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