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Article: Outcome of management based on "1+X" model in a health examination center.

Dou, Zhiyong / Li, Xuyan

American journal of translational research

2023 Volume 15, Issue 9, Page(s) 5891–5899

Abstract: Objective: To investigate the effect of management measures based on the "1+X" model in physical examination centers.: Methods: This retrospective study was conducted on 5362 individuals who underwent physical examinations in Heping Hospital ... ...

Abstract	Objective: To investigate the effect of management measures based on the "1+X" model in physical examination centers. Methods: This retrospective study was conducted on 5362 individuals who underwent physical examinations in Heping Hospital Affiliated to Changzhi Medical College from January 1, 2020 to December 31, 2022. These subjects were divided into an observation group (n=2681) and a control group (n=2681) according to the different management measures. Subjects from the control group were given routine management measures, while those from the observation group were given management measures based on the "1+X" model. The scores of negative emotions, waiting time for physical examination, acquisition of health knowledge, satisfaction for the physical examinations, and efficiency and degree of credibility in medical management were evaluated and compared between the two groups. Results: After management, the scores of anxiety and depression in both groups were significantly reduced in contrast to before management, and the two scores were significantly lower in the observation group than those in the control group (P<0.05). The observation group experienced significantly shorter waiting time for routine urination, blood sampling, internal and surgical examinations, and electrocardiogram than the control group (all P<0.001). The acquisition of health knowledge in the observation group was significantly better than that in the control group (P<0.05). The satisfaction rates of the observation group in the terms of service attitude, examination environment, health education, and follow-up services were significantly better than those in the control group (all P<0.05). Moreover, the efficiency and degree of credibility in medical management in the observation group were better than those in the control group. Conclusion: The application of management measures based on the "1+X" model has a good effect in our physical examination center. On the one hand, it can significantly reduce the waiting time for various physical examinations and alleviate the negative emotions of physical examinees. On the other hand, it can effectively enhance the overall acquisition of health knowledge, the satisfaction of physical examination, and the efficiency and degree of credibility in medical management. This management model is worthy of clinical promotion and application.
Language	English
Publishing date	2023-09-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	2471058-1
ISSN	1943-8141
ISSN	1943-8141
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Clinical features and prognosis of pediatric idiopathic sudden sensorineural hearing loss: A bi-center retrospective study.

Li, Yingqiang / Zhou, Xiaowei / Dou, Zhiyong / Deng, Dongzhou / Bing, Dan

Frontiers in neurology

2023 Volume 14, Page(s) 1121656

Abstract: Objective: Limited research has focused on the clinical features of sudden sensorineural hearing loss (SSNHL) in pediatric patients. This study is aimed to investigate the relationship between clinical features and the baseline hearing severity and ... ...

Abstract	Objective: Limited research has focused on the clinical features of sudden sensorineural hearing loss (SSNHL) in pediatric patients. This study is aimed to investigate the relationship between clinical features and the baseline hearing severity and outcomes of SSNHL in the pediatric population. Method: We conducted a bi-center retrospective observational study in 145 SSNHL patients aged no more than 18 years who were recruited between November 2013 and October 2022. Data extracted from medical records, audiograms, complete blood count (CBC) and coagulation tests have been assessed for the relationship with the severity (the thresholds of the initial hearing) and outcomes (recovery rate, hearing gain and the thresholds of the final hearing). Results: A lower lymphocyte count ( Conclusions: The present study showed that accompanying tinnitus, the severity of initial hearing loss, the time elapse and the audiogram configuration might be related to the prognosis of pediatric SSNHL. Meanwhile, the presence of vertigo, lower lymphocytes and higher PLR were associated with worse severity.
Language	English
Publishing date	2023-03-15
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2564214-5
ISSN	1664-2295
ISSN	1664-2295
DOI	10.3389/fneur.2023.1121656
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Article ; Online: Knowledge and coping style about depression in medical students: A cross-sectional study in China.

Lian, Yajun / Yan, Yumeng / Ping, Weiwei / Dou, Zhiyong / Wang, Xiaoyan / Yang, Hui

PloS one

2023 Volume 18, Issue 10, Page(s) e0293511

Abstract: Objectives: The current study aimed at ascertaining the depression levels of medical students and their knowledge levels of depression, and exploring the relationship between the level of knowledge and coping styles of the medical students on depression. ...

Abstract	Objectives: The current study aimed at ascertaining the depression levels of medical students and their knowledge levels of depression, and exploring the relationship between the level of knowledge and coping styles of the medical students on depression. Methods: An online-based survey was developed in Changzhi Medical College. The questionnaire included demographic and socioeconomic data, questions about depression knowledge and copying styles of depression, and the Zung Self-Rating Depression Scale (SDS). A total of 1931 questionnaires were returned by respondents. Results: The medical students produced a mean SDS score of 44.29 (SD = 11.67). The prevalence of depression was 29.7%. Sophomore, female, and poor family relationships were parameters associated with a higher SDS score. The total correct rate for knowledge of depression was 64.14%. There were statistical differences between with depression students and non-depression students on the rate of the correct answers in the following questions:"Female has more probability", "Depression can be adjusted by oneself", "Associated with one's character", "Know cure method of depression", "Know drug use of depression", "Know depression influence for health", and "Know prevention method of depression". Depression students were more likely to have a lower rate of correct answer for above questions. Asking for help from psychological consultation was the primary coping mechanism among the medical students. The logistic regression analysis results found that depressed students who chose the coping way of no ways of coping were more likely to be females OR = 1.470 (1.078, 2.005), residents in rural area OR = 1.496 (1.038, 2.156), in poor family relationships OR = 2.428 (1.790, 3.293), and have lower cognitive level of depression knowledge OR = 1.920 (1.426, 3.226). Conclusions: It is necessary to focus on mental health of medical students, especially in female, residents in rural area, in poor family relationships, and having lower cognitive level of depression knowledge. Medical students were insufficient on depression knowledge and coping styles, and efforts that train students know risk of impaired mental health could also improve diagnosis and treatment.
MeSH term(s)	Humans ; Female ; Male ; Students, Medical/psychology ; Cross-Sectional Studies ; Depression/epidemiology ; Depression/psychology ; Adaptation, Psychological ; China/epidemiology ; Surveys and Questionnaires
Language	English
Publishing date	2023-10-27
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0293511
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Article ; Online: Pure tone audiogram classification using deep learning techniques.

Dou, Zhiyong / Li, Yingqiang / Deng, Dongzhou / Zhang, Yunxue / Pang, Anran / Fang, Cong / Bai, Xiang / Bing, Dan

Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery

2024

Abstract: Objective: Pure tone audiometry has played a critical role in audiology as the initial diagnostic tool, offering vital insights for subsequent analyses. This study aims to develop a robust deep learning framework capable of accurately classifying ... ...

Abstract	Objective: Pure tone audiometry has played a critical role in audiology as the initial diagnostic tool, offering vital insights for subsequent analyses. This study aims to develop a robust deep learning framework capable of accurately classifying audiograms across various commonly encountered tasks. Design, setting, and participants: This single-centre retrospective study was conducted in accordance with the STROBE guidelines. A total of 12 518 audiograms were collected from 6259 patients aged between 4 and 96 years, who underwent pure tone audiometry testing between February 2018 and April 2022 at Tongji Hospital, Tongji Medical College, Wuhan, China. Three experienced audiologists independently annotated the audiograms, labelling the hearing loss in degrees, types and configurations of each audiogram. Main outcome measures: A deep learning framework was developed and utilised to classify audiograms across three tasks: determining the degrees of hearing loss, identifying the types of hearing loss, and categorising the configurations of audiograms. The classification performance was evaluated using four commonly used metrics: accuracy, precision, recall and F1-score. Results: The deep learning method consistently outperformed alternative methods, including K-Nearest Neighbors, ExtraTrees, Random Forest, XGBoost, LightGBM, CatBoost and FastAI Net, across all three tasks. It achieved the highest accuracy rates, ranging from 96.75% to 99.85%. Precision values fell within the range of 88.93% to 98.41%, while recall values spanned from 89.25% to 98.38%. The F1-score also exhibited strong performance, ranging from 88.99% to 98.39%. Conclusions: This study demonstrated that a deep learning approach could accurately classify audiograms into their respective categories and could contribute to assisting doctors, particularly those lacking audiology expertise or experience, in better interpreting pure tone audiograms, enhancing diagnostic accuracy in primary care settings, and reducing the misdiagnosis rate of hearing conditions. In scenarios involving large-scale audiological data, the automated classification system could be used as a research tool to efficiently provide a comprehensive overview and statistical analysis. In the era of mobile audiometry, our deep learning framework can also help patients quickly and reliably understand their self-tested audiograms, potentially encouraging timely consultations with audiologists for further evaluation and intervention.
Language	English
Publishing date	2024-05-15
Publishing country	England
Document type	Journal Article
ZDB-ID	2205891-6
ISSN	1749-4486 ; 1749-4478 ; 0307-7772 ; 1365-2273
ISSN (online)	1749-4486
ISSN	1749-4478 ; 0307-7772 ; 1365-2273
DOI	10.1111/coa.14170
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Article ; Online: Effects of soil properties on heavy metal bioavailability and accumulation in crop grains under different farmland use patterns.

Xu, Decong / Shen, Zhangjun / Dou, Changming / Dou, Zhiyong / Li, Yang / Gao, Yi / Sun, Qingye

Scientific reports

2022 Volume 12, Issue 1, Page(s) 9211

Abstract: Mining activities have increased the accumulation of heavy metals in farmland soil and in food crops. To identify the key soil properties influencing heavy metal bioavailability and accumulation in food crops, 81 crop samples and 81 corresponding ... ...

Abstract	Mining activities have increased the accumulation of heavy metals in farmland soil and in food crops. To identify the key soil properties influencing heavy metal bioavailability and accumulation in food crops, 81 crop samples and 81 corresponding agricultural soil samples were collected from rape, wheat, and paddy fields. Heavy metal (copper (Cu), zinc (Zn), lead (Pb), cadmium (Cd), iron (Fe), and manganese (Mn)) concentrations in soils and rape, wheat, rice grains were determined using inductively coupled plasma atomic emission spectroscopy, and soil physicochemical properties (pH, organic matter, total nitrogen, total phosphorus, available phosphorus, and available potassium (AK)) were analyzed. Soil extractable metals were extracted using various single extractants (DTPA, EDTA, NH
MeSH term(s)	Biological Availability ; Cadmium ; Crops, Agricultural ; Farms ; Lead ; Metals, Heavy/analysis ; Oryza/chemistry ; Phosphorus ; Soil/chemistry ; Soil Pollutants/analysis ; Triticum/chemistry
Chemical Substances	Metals, Heavy ; Soil ; Soil Pollutants ; Cadmium (00BH33GNGH) ; Phosphorus (27YLU75U4W) ; Lead (2P299V784P)
Language	English
Publishing date	2022-06-02
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-022-13140-1
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Book ; Online: Learning Global and Local Consistent Representations for Unsupervised Image Retrieval via Deep Graph Diffusion Networks

Dou, Zhiyong / Cui, Haotian / Zhang, Lin / Wang, Bo

2020

Abstract: Diffusion has shown great success in improving accuracy of unsupervised image retrieval systems by utilizing high-order structures of image manifold. However, existing diffusion methods suffer from three major limitations: 1) they usually rely on local ... ...

Abstract	Diffusion has shown great success in improving accuracy of unsupervised image retrieval systems by utilizing high-order structures of image manifold. However, existing diffusion methods suffer from three major limitations: 1) they usually rely on local structures without considering global manifold information; 2) they focus on improving pair-wise similarities within existing images input output transductively while lacking flexibility to learn representations for novel unseen instances inductively; 3) they fail to scale to large datasets due to prohibitive memory consumption and computational burden due to intrinsic high-order operations on the whole graph. In this paper, to address these limitations, we propose a novel method, Graph Diffusion Networks (GRAD-Net), that adopts graph neural networks (GNNs), a novel variant of deep learning algorithms on irregular graphs. GRAD-Net learns semantic representations by exploiting both local and global structures of image manifold in an unsupervised fashion. By utilizing sparse coding techniques, GRAD-Net not only preserves global information on the image manifold, but also enables scalable training and efficient querying. Experiments on several large benchmark datasets demonstrate effectiveness of our method over state-of-the-art diffusion algorithms for unsupervised image retrieval.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006 ; 004
Publishing date	2020-01-05
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: [Distribution Characteristics of Nitrifiers and Denitrifiers in the River Sediments of Tongling City].

Cheng, Jian-hua / Dou, Zhi-yong / Sun, Qing-ye

Huan jing ke xue= Huanjing kexue

2016 Volume 37, Issue 4, Page(s) 1362–1370

Abstract: Rivers in mining areas were influenced by contaminants such as nitrogen, phosphorus and organic matter due to domestic and agricultural wastewater discharge in addition to pollutants caused by mining activities. In this study, surface sediment samples of ...

Abstract	Rivers in mining areas were influenced by contaminants such as nitrogen, phosphorus and organic matter due to domestic and agricultural wastewater discharge in addition to pollutants caused by mining activities. In this study, surface sediment samples of rivers in Tongling city were collected to address the effect of season and pollution type on the abundance of nitrifiers and denitrifiers using quantitative polymerase chain reaction (QPCR) technique targeting at the ammonia monooxygenase (amoA) and nitrite reductase (nir) genes. The results showed that the average ahundance of ammonia oxidizing archaea (AGA) (ranging from 1.74 x 10⁵ to 1.45 x 10⁸ copies · g⁻¹) was 4.39 times that of ammonia oxidizing hacteria (AGH) (ranging from 1.39 x 10⁵ to 3.39 x 10⁷ copies · g⁻¹); and the average abundance of nirK gene (ranging from 4.45 x 10⁶ to 1.51 x 10⁸ copies · g) was almost a thirtieth part of nirS gene (ranging from 1.69 x 10⁷ to 8.55 x 10⁹ copies · g⁻¹). The abundance of AOA was higher in spring and autumn, and lower in summer and winter. And sediment AOB abundance was higher in spring and winter than in summer and autumn. Meanwhile, the abundance of nir genes was in the order of spring (nirS )/autumn (nirK) > summer > winter > autumn (nirS )/spring (nirK). Moreover, the abundance of bacterial and archaeal arnoA and nirS genes in sediments influenced by mine pollution was generally higher than that in sediments influenced by agricultural non-point pollution, whereas the abundance of nirK gene showed an opposite trend.
MeSH term(s)	Ammonia/analysis ; Archaea/genetics ; Archaea/isolation & purification ; Bacteria/genetics ; Bacteria/isolation & purification ; China ; Cities ; Denitrification ; Environmental Monitoring ; Genes, Archaeal ; Genes, Bacterial ; Geologic Sediments/microbiology ; Nitrification ; Nitrite Reductases/genetics ; Nitrogen/analysis ; Oxidation-Reduction ; Oxidoreductases/genetics ; Rivers/microbiology ; Seasons
Chemical Substances	Ammonia (7664-41-7) ; Oxidoreductases (EC 1.-) ; Nitrite Reductases (EC 1.7.-) ; ammonia monooxygenase (EC 1.7.3.-) ; Nitrogen (N762921K75)
Language	Chinese
Publishing date	2016-04-15
Publishing country	China
Document type	English Abstract ; Journal Article
ISSN	0250-3301
ISSN	0250-3301
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Long-term SARS-CoV-2 neutralizing antibody level prediction using multimodal deep learning: A prospective cohort study on longitudinal data in Wuhan, China.

Fang, Cong / Yan, Weiming / Chen, Yuying / Dou, Zhiyong / Liu, Tingting / Luo, Fengning / Chen, Weiwei / Li, Xitang / Chen, Yajie / Wu, Wenhui / Yuan, Zhize / Niu, Yuxin / Wang, Peng / Zhu, Wenzhen / Luo, Xiaoping / Chen, Tao / Bai, Xiang / Wang, Xiaojing / Ning, Qin

Journal of medical virology

2023 Volume 95, Issue 8, Page(s) e29036

Abstract: The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people worldwide. Assessing the level and duration of SARS-CoV-2 neutralizing antibody (Nab) would provide key information for government to make sound healthcare ... ...

Abstract	The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people worldwide. Assessing the level and duration of SARS-CoV-2 neutralizing antibody (Nab) would provide key information for government to make sound healthcare policies. Assessed at 3-, 6-, 12-, and 18-month postdischarge, we described the temporal change of IgG levels in 450 individuals with moderate to critical COVID-19 infection. Moreover, a data imputation framework combined with a novel deep learning model was implemented to predict the long-term Nab and IgG levels in these patients. Demographic characteristics, inspection reports, and CT scans during hospitalization were used in this model. Interpretability of the model was further validated with Shapely Additive exPlanation (SHAP) and Gradient-weighted Class Activation Mapping (GradCAM). IgG levels peaked at 3 months and remained stable in 12 months postdischarge, followed by a significant decline in 18 months postdischarge. However, the Nab levels declined from 6 months postdischarge. By training on the cohort of 450 patients, our long-term antibody prediction (LTAP) model could predict long-term IgG levels with relatively high area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1-score, which far exceeds the performance achievable by commonly used models. Several prognostic factors including FDP levels, the percentages of T cells, B cells and natural killer cells, older age, sex, underlying diseases, and so forth, served as important indicators for IgG prediction. Based on these top 15 prognostic factors identified in IgG prediction, a simplified LTAP model for Nab level prediction was established and achieved an AUC of 0.828, which was 8.9% higher than MLP and 6.6% higher than LSTM. The close correlation between IgG and Nab levels making it possible to predict long-term Nab levels based on the factors selected by our LTAP model. Furthermore, our model identified that coagulation disorders and excessive immune response, which indicate disease severity, are closely related to the production of IgG and Nab. This universal model can be used as routine discharge tests to identify virus-infected individuals at risk for recurrent infection and determine the optimal timing of vaccination for general populations.
MeSH term(s)	Humans ; Antibodies, Neutralizing ; SARS-CoV-2 ; Aftercare ; Deep Learning ; Prospective Studies ; COVID-19/diagnosis ; Patient Discharge ; China/epidemiology ; Antibodies, Viral ; Immunoglobulin G
Chemical Substances	Antibodies, Neutralizing ; Antibodies, Viral ; Immunoglobulin G
Language	English
Publishing date	2023-08-25
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	752392-0
ISSN	1096-9071 ; 0146-6615
ISSN (online)	1096-9071
ISSN	0146-6615
DOI	10.1002/jmv.29036
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Article ; Online: Health protective behavior scale: Development and psychometric evaluation.

Ping, Weiwei / Cao, Wenjun / Tan, Hongzhuan / Guo, Chongzheng / Dou, Zhiyong / Yang, Jianzhou

PloS one

2018 Volume 13, Issue 1, Page(s) e0190390

Abstract: Objective: A healthy lifestyle includes health protective and health promoting behaviors. Health promoting lifestyle profiles have been developed, but measures of health protective behavior are still lacking. This study sought to develop a health ... ...

Abstract	Objective: A healthy lifestyle includes health protective and health promoting behaviors. Health promoting lifestyle profiles have been developed, but measures of health protective behavior are still lacking. This study sought to develop a health protecting behavior scale. Methods: An initial item pool for the Health Protective Behavior Scale (HPBS) was generated based on read and referred literature and a single-item open-ended survey. An expert group screened this initial item pool using an item-level content validity index. Pilot testing was conducted. The degree of variation, the response rate, the item-total correlation coefficient, and the factor loading in factor analysis and item analysis were used to screen items using data of pilot testing. 454 subjects were recruited evaluate the psychometric properties of the HPBS. Analyses included internal consistency, test-retest reliability, factor analysis, parallel analysis, correlation analysis and criterion validity analysis. Results: The final iteration of the HPBS was developed with 32 items and five dimensions: interpersonal support, general behavior, self-knowledge, nutrition behavior and health care. Cronbach's alpha coefficient, and test-retest reliability were 0.89 and 0.89 respectively. Correlation coefficients of the five dimensions ranged from 0.28 to 0.55. The Spearman correlation coefficient between the total scores on the WHOQOL-BREF and on the HPBS was 0.34. Conclusions: HPBS has sufficient validity and reliability to measure health protective behaviors in adults.
MeSH term(s)	Health Promotion/organization & administration ; Humans ; Life Style ; Psychometrics
Language	English
Publishing date	2018
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0190390
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Deep-Person

Bai, Xiang / Yang, Mingkun / Huang, Tengteng / Dou, Zhiyong / Yu, Rui / Xu, Yongchao

Learning Discriminative Deep Features for Person Re-Identification

2017

Abstract: Recently, many methods of person re-identification (Re-ID) rely on part-based feature representation to learn a discriminative pedestrian descriptor. However, the spatial context between these parts is ignored for the independent extractor to each ... ...

Abstract	Recently, many methods of person re-identification (Re-ID) rely on part-based feature representation to learn a discriminative pedestrian descriptor. However, the spatial context between these parts is ignored for the independent extractor to each separate part. In this paper, we propose to apply Long Short-Term Memory (LSTM) in an end-to-end way to model the pedestrian, seen as a sequence of body parts from head to foot. Integrating the contextual information strengthens the discriminative ability of local representation. We also leverage the complementary information between local and global feature. Furthermore, we integrate both identification task and ranking task in one network, where a discriminative embedding and a similarity measurement are learned concurrently. This results in a novel three-branch framework named Deep-Person, which learns highly discriminative features for person Re-ID. Experimental results demonstrate that Deep-Person outperforms the state-of-the-art methods by a large margin on three challenging datasets including Market-1501, CUHK03, and DukeMTMC-reID. Specifically, combining with a re-ranking approach, we achieve a 90.84% mAP on Market-1501 under single query setting. Comment: Accepted to Pattern Recognition. The code is released: https://github.com/zydou/Deep-Person
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006 ; 004
Publishing date	2017-11-28
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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