The Artificial intelligence large language models and neuropsychiatry practice and research ethic

神经精神病学 心理学 认知科学 精神科
作者
Yi Zhong,Yujun Chen,Yang Zhou,Yan-Ao-Hai Lyu,Jiajun Yin,Yujun Gao
出处
期刊:Asian Journal of Psychiatry [Elsevier BV]
卷期号:84: 103577-103577 被引量:44
标识
DOI:10.1016/j.ajp.2023.103577
摘要

Previous studies have revealed the frontoparietal network (FPN) plays a key role in the imaging pathophysiology of bipolar disorder (BD). However, network homogeneity (NH) in the FPN among bipolar mania (BipM), remitted bipolar disorder (rBD), and healthy controls (HCs) remains unknown. The present study aimed to explore whether NH within the FPN can be used as an imaging biomarker to differentiate BipM from rBD and to predict treatment efficacy for patients with BipM.Sixty-six patients with BD (38 BipM and 28 rBD) and 60 HCs participated in resting-state functional magnetic resonance imaging and neuropsychological tests. Independent component analysis and NH analysis were applied to analyze the imaging data.Relative to HCs, BipM patients displayed increased NH in the left middle frontal gyrus (MFG), and rBD patients displayed increased NH in the right inferior parietal lobule (IPL). Compared to rBD patients, BipM patients displayed reduced NH in the right IPL. Furthermore, support vector machine results exhibited that NH values in the right IPL could distinguish BipM patients from rBD patients with 69.70 %, 57.89 %, and 91.67 % for accuracy, sensitivity, and specificity, respectively, and support vector regression results exhibited a significant association between predicted and actual symptomatic improvement based on the reduction ratio of the Young` Mania Rating Scale total scores (r = 0.466, p < 0.01).The study demonstrated distinct NH values in the FPN could serve as a valuable neuroimaging biomarker capable of differentiating patients with BipM and rBD, and NH values of the left MFG as a potential predictor of early treatment response in patients with BipM.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
nico完成签到,获得积分10
1秒前
偏执发布了新的文献求助10
1秒前
李子啊完成签到 ,获得积分10
1秒前
要减肥的安柏完成签到 ,获得积分10
2秒前
3秒前
Garcia完成签到,获得积分10
5秒前
momo发布了新的文献求助10
5秒前
不明完成签到 ,获得积分10
7秒前
KK_ad完成签到,获得积分10
7秒前
小楼发布了新的文献求助10
8秒前
dgfhg完成签到,获得积分20
8秒前
9秒前
HUI完成签到,获得积分10
10秒前
10秒前
烟花应助东风渡采纳,获得10
11秒前
liugm发布了新的文献求助10
11秒前
dgfhg发布了新的文献求助30
11秒前
nico发布了新的文献求助10
11秒前
cy完成签到 ,获得积分10
12秒前
顺利白竹完成签到 ,获得积分10
12秒前
JasonChan完成签到 ,获得积分10
13秒前
Lotto发布了新的文献求助10
14秒前
15秒前
lidie发布了新的文献求助10
18秒前
19秒前
JamesPei应助科研通管家采纳,获得10
20秒前
华仔应助科研通管家采纳,获得10
20秒前
优秀水蓝应助科研通管家采纳,获得30
20秒前
研友_VZG7GZ应助科研通管家采纳,获得10
20秒前
郭子啊完成签到 ,获得积分10
20秒前
bkagyin应助科研通管家采纳,获得10
20秒前
顾矜应助科研通管家采纳,获得10
20秒前
稳重诗珊发布了新的文献求助10
20秒前
20秒前
ROY发布了新的文献求助10
20秒前
20秒前
852应助科研通管家采纳,获得10
20秒前
慕青应助科研通管家采纳,获得10
20秒前
Copyright应助科研通管家采纳,获得10
20秒前
21秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Development of a Bridge Weigh-In-Motion System: A technology to convert the bridge response to the passage of traffic into data on vehicle configurations, speeds, times of travel and weights 1000
Molecular Mechanisms of Photosynthesis, 4th Edition 1000
Organic Reactions, Volume 116 1000
Current concepts in cutaneous toxicity : proceedings of the Fourth Conference on Cutaneous Toxicity, Washington, D.C., May 9-11, 1979 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7265189
求助须知:如何正确求助?哪些是违规求助? 8886174
关于积分的说明 18780494
捐赠科研通 6942844
什么是DOI,文献DOI怎么找? 3202849
关于科研通互助平台的介绍 2376018
邀请新用户注册赠送积分活动 2178779