Predicting Delayed Neurocognitive Recovery After Non-cardiac Surgery Using Resting-State Brain Network Patterns Combined With Machine Learning
Delayed neurocognitive recovery (DNR) is a common subtype of postoperative neurocognitive disorders. An objective approach for identifying subjects at high risk of DNR is yet lacking. The present study aimed to predict DNR using the machine learning method based on multiple cognitive-related brain n...
Enregistré dans:
Auteurs principaux: | Zhaoshun Jiang, Yuxi Cai, Xixue Zhang, Yating Lv, Mengting Zhang, Shihong Li, Guangwu Lin, Zhijun Bao, Songbin Liu, Weidong Gu |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Frontiers Media S.A.
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/e35e10e114bd49b58cc8f99b3589b3fa |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Association between preoperative serum homocysteine and delayed neurocognitive recovery after non-cardiac surgery in elderly patients: a prospective observational study
par: Zhen-Feng Zhang, et autres
Publié: (2021) -
Resting-state functional connectivity changes within the default mode network and the salience network after antipsychotic treatment in early-phase schizophrenia
par: Wang Y, et autres
Publié: (2017) -
Changes of Brain Functional Connectivity in End-Stage Renal Disease Patients Receiving Peritoneal Dialysis Without Cognitive Decline
par: Ting-Yu Chang, et autres
Publié: (2021) -
Cognitive Deficiency in Cannabis Consumers
par: Wurgan Rahadian, et autres
Publié: (2021) -
Abnormal Network Homogeneity in the Right Superior Medial Frontal Gyrus in Cervical Dystonia
par: Shubao Wei, et autres
Publié: (2021)