A comprehensive review for machine learning on neuroimaging in obsessive-compulsive disorder

被引:2
|
作者
Li, Xuanyi [1 ]
Kang, Qiang [2 ]
Gu, Hanxing [3 ]
机构
[1] China Med Univ, Shengjing Hosp, Dept Radiol, Shenyang, Liaoning, Peoples R China
[2] Xingan League Peoples Hosp Inner Mongolia, Dept Radiol, Ulanhot, Mongolia, Peoples R China
[3] Qingdao Mental Hlth Ctr, Dept Geriatr Psychiat, Qingdao, Shandong, Peoples R China
来源
FRONTIERS IN HUMAN NEUROSCIENCE | 2023年 / 17卷
关键词
neuroimaging; MRI; machine learning; obsessive-compulsive disorder; AI; SEROTONIN REUPTAKE INHIBITORS; POSTTRAUMATIC-STRESS-DISORDER; MULTIVARIATE PATTERN-ANALYSIS; ANXIETY DISORDERS; DOUBLE-BLIND; PHARMACOLOGICAL-TREATMENTS; SYMPTOM IMPROVEMENT; BEHAVIORAL-THERAPY; WHITE-MATTER; AUGMENTATION;
D O I
10.3389/fnhum.2023.1280512
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Obsessive-compulsive disorder (OCD) is a common mental disease, which can exist as a separate disease or become one of the symptoms of other mental diseases. With the development of society, statistically, the incidence rate of obsessive-compulsive disorder has been increasing year by year. At present, in the diagnosis and treatment of OCD, The clinical performance of patients measured by scales is no longer the only quantitative indicator. Clinical workers and researchers are committed to using neuroimaging to explore the relationship between changes in patient neurological function and obsessive-compulsive disorder. Through machine learning and artificial learning, medical information in neuroimaging can be better displayed. In this article, we discuss recent advancements in artificial intelligence related to neuroimaging in the context of Obsessive-Compulsive Disorder.
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页数:16
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