Yuxiu Sui's research while affiliated with Nanjing Medical University and other places

Publications (23)

Article
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Background There is limited evidence on the efficacy of electroconvulsive therapy (ECT) in adolescents with mental illness. The present study reported outcomes of adolescents with mental illness treated with ECT aimed at providing evidence for large-scale feasibility. Objectives The primary objective of this trial was to examine the differences in...
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Background Schizophrenia (SZ) is associated with the highest disability rate among serious mental disorders. Excited symptoms are the core symptoms of SZ, which appear in the early stage, followed by other stages of the disease subsequently. These symptoms are destructive and more prone to violent attacks, posing a serious economic burden to the so...
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Impaired capability for understanding and interpreting the expressions on other people's faces manifests itself as a core feature of schizophrenia, contributing to social dysfunction. With the purpose of better understanding of the neurobiological basis of facial emotion perception deficits in schizophrenia, we investigated facial emotion perceptio...
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Objective The aim of this study was to explore health anxiety (HA) in a sample of hospital medical employees and to identify factors that influence HA. Methods A consecutively recruited sample of 1702 medical employees with or without HA was obtained from 13 hospitals across China. Participants’ demographic and clinical characteristics were collec...
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Several resting-state neuroimaging studies have indicated abnormal regional homogeneity (ReHo) in chronic schizophrenia; however, little work has been conducted to investigate naïve patients with first-episode schizophrenia (FES). Even less investigated is the association between ReHo measures and clinical symptom severity in naïve patients with FE...
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Misdiagnosis between major depressive disorder (MDD) and bipolar depression (BD) is quite common. Our previous study found significantly lower serum VGF (non‐acronymic) in MDD patients. However, it is unclear whether same changes occur in BD patients. Therefore, we aimed to investigate the relationship between serum VGF levels in BD and MDD patient...
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(Aim) Alcohol use disorder may put health at risk and cause serious health problems. It is of increasing importance to identify alcohol use disorder as early as possible. (Method) This study proposed a computer-vision based technique. The dataset was scanned by magnetic resonance imaging in China participating hospitals. Afterwards, we combined wav...
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Background: The number of patients with Alzheimer's disease is increasing rapidly every year. Scholars often use computer vision and machine learning methods to develop an automatic diagnosis system. Objective: In this study, we developed a novel machine learning system that can make diagnoses automatically from brain magnetic resonance images....
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Background The impairment of cognitive function is one of the core symptoms in schizophrenia, and the degree of recovery is closely related to whether patients are able to rejoin society successfully. Objective This study was to clarify the correlation between cognitive function and cerebral grey matter volume in schizophrenia. Methods The neuro-...
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Alzheimer’s disease (AD) is a progressive brain disease. The goal of this study is to provide a new computer-vision based technique to detect it in an efficient way. The brain-imaging data of 98 AD patients and 98 healthy controls was collected using data augmentation method. Then, convolutional neural network (CNN) was used, CNN is the most succes...
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The alcohol use disorder (AUD) is an important brain disease, which could cause the damage and alteration of brain structure. The current diagnosis of AUD is mainly done manually by radiologists. This study proposes a novel computer-vision-based method for automatic detection of AUD based on wavelet Renyi entropy and three-segment encoded Jaya algo...
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Mental disorders are severe, disabling conditions with unknown etiology and are commonly misdiagnosed when clinical symptomology criteria are solely used. Our previous work indicated that combination of serum levels of multiple proteins in tissue plasminogen activator (tPA)-brain-derived neurotrophic factor (BDNF) pathway improved accuracy of diagn...
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Alcohol use disorder (AUD) is an important brain disease. It alters the brain structure. Recently, scholars tend to use computer vision based techniques to detect AUD. We collected 235 subjects, 114 alcoholic and 121 non-alcoholic. Among the 235 image, 100 images were used as training set, and data augmentation method was used. The rest 135 images...
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Background: Facial emotion perception is impaired in schizophrenia. Although the pathology of schizophrenia is thought to involve abnormality in white matter (WM), few studies have examined the correlation between facial emotion perception and WM abnormalities in never-medicated patients with first-episode schizophrenia. The present study tested a...
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Full-text available
To identify the association between the functional and structural changes of default mode network (DMN) underlying the cognitive impairment in Late-onset depression (LOD), 32 LOD patients and 39 normal controls were recruited and underwent resting-state fMRI, DTI scans, and cognitive assessments. Seed-based correlation analysis was conducted to exp...
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The intuitive association between cognitive impairment and aberrant functional activity in the brain network has prompted interest in exploring the role of functional connectivity in late-onset depression (LOD). The relationship of altered voxel-mirrored homotopic connectivity (VMHC) and cognitive dysfunction in LOD is not yet well understood. This...
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Multitasking refers to the ability to organize assorted tasks efficiently in a short period of time, which plays an important role in daily life. However, the structural neural correlates of multitasking performance remain unclear. The present study aimed at exploring the brain regions associated with multitasking performance using global correlati...
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Background The intuitive association between cognitive dysfunction in late onset depression (LOD) and the aberrant functional activity in the brain's default-mode network (DMN) has prompted interest in exploring the role of the DMN in LOD. The altered pattern of resting state voxel-mirrored homotopic connectivity (VMHC) in cognitive processes is no...
Article
To investigate the relationship between hippocampal functional connectivity (HFC), cognitive deficits, and the influence of BDNF Val66Met polymorphism on the HFC in acute late-onset depression (LOD). 26 LOD patients and 33 and normal controls (NCs) completed clinical assessments, neuropsychological testing, blood samples collecting for genotyping,...
Article
The objective of the study is to investigate the relationship between altered resting-state cortico-cerebellar functional connectivity (FC) and depression as well as cognitive impairment in late-onset depression (LOD). A total of 32 LOD and 39 well-matched normal controls (NCs) were recruited and underwent resting-state functional MRI (R-fMRI) scan...

Citations

... Chen ve arkadaşlarının [33] bir sağlık kurumunda yaptığı çalışmada, düşük gelir düzeyinin sağlık kaygısı için risk faktörü oluşturduğu görülmüştür. Çalışmanın bir diğer sonucu ise düşük eğitim seviyesi daha yüksek sağlık kaygısı oranı ile ilişkilendirilmiştir. Mapelli, okuryazar olmayanların kaygı düzeylerini yüksek bulmuştur. ...
... Irritability is nearly ubiquitous in childhood psychopathology. Children with major depressive disorder, dysthymic disorder, or oppositional de iant disorder routinely experience irritable moods [15]. ...
... In the behavioural test, we adopted a visual search task to behaviourally measure the FER ability in schizophrenia, which is more concerned with the detection and identification of stimuli compared with the match-tosample task 26 . Regarding accuracy, similar to the findings of most previous studies, our test showed that patients with FSZ performed worse in FER than HCs 27,28 . Furthermore, only the interaction between stimulus and group was significant, which may be caused by the fact that the accuracy of FER in schizophrenia was impaired more severely for fearful facial emotion than happy facial emotion. ...
... For example, some studies only found decreased ReHo 10,11 , while others only observed increased ReHo in patients with schizophrenia 12,13 . Additionally, in separate studies, ReHo was also found to decrease or increase in different brain regions in patients with schizophrenia 14,15 . This discrepancy may be attributed to between-study variations in demographic and clinical characteristics of patients, and approaches of image data acquisition and analysis; the relatively small sample size in these studies may also account for the distinct findings. ...
... The fully connected layers are the most common structure in artificial neural networks [13,19,20,26]. Every node in the layer is connected to all the nodes in the adjacent layer. ...
... An artificial neuron is a sort of cell that functions similarly to a real neuron because it accepts several inputs, does calculations, and outputs the result [43][44][45][46][47]. This straightforward calculation uses a nonlinear activation function before a linear source regular expression form [48]. Several often utilized nonlinear network activation functions include the sigmoid conversion, ReLU, their variations, and tanh (hyperbolic tangent) [49][50][51][52][53]. Deep learning's development roots may be found in the work of Walter Pitts and Warren McCulloch (1943). ...
... Edge computing is increasingly used in medical IoT scenarios due to the advantage of reducing the burden on network infrastructure caused by the increasing number of IoT devices. Combined with CT images which are widely available, this paper [13] proposes a 3D reconstruction method of CT images [14] [15] [16] [14][15][16]in Internet of Things based on edge computing. For speckle noise [17] in CT, a multi-stage feature extraction generative adversarial network (MF-GAN) denoising algorithm is used to ensure texture and edge reconstruction. ...
... In a convolutional neural network, an element in the output of a certain layer is determined when the region size of the corresponding input layer is called the receptive field. The new feature mapping can convolution the input with the learning filter [18], and then apply the nonlinear activation function to the convolutional result to obtain the output result [19][20][21]. The filters in the low convolutional layer are used to detect low-order features such as linear textures at edges and corners. ...
... Previous research showed that NGFR is involved in neurogenesis, regulation of sprouting, synaptogenesis and pruning, which contributes to altered neural functions, and is thought to be the basis of psychiatric disorders [14][15][16]. Studies showed that the serum NGFR levels in patients with depression [17,18], schizophrenia [19] and bipolar disorder [20] were significantly different from those in healthy controls. NGFR gene polymorphisms were reported to be associated with depression, schizophrenia and antidepressant efficacy [21,22]. ...
... Inequality constraints and the resolution of a quadratic programming issue were converted into equality constraints and the resolution of linear equations, respectively, by LSSVRM [22]. Then, by introducing whale optimization algorithm into LSSVRM, we refined the kernel function parameter selection approach to increase operational efficiency [23]. ...