In order to address the issues of spatial induction bias and lack of effective representation of global contextual information in colon polyp image segmentation, which lead to the loss of edge details and mis-segmentation of lesion areas, a colon polyp segmentation method that combines Transformer and cross-level phase-awareness is proposed. The method started from the perspective of global feature transformation, and used a hierarchical Transformer encoder to extract semantic information and spatial details of lesion areas layer by layer. Secondly, a phase-aware fusion module (PAFM) was designed to capture cross-level interaction information and effectively aggregate multi-scale contextual information. Thirdly, a position oriented functional module (POF) was designed to effectively integrate global and local feature information, fill in semantic gaps, and suppress background noise. Fourthly, a residual axis reverse attention module (RA-IA) was used to improve the network's ability to recognize edge pixels. The proposed method was experimentally tested on public datasets CVC-ClinicDB, Kvasir, CVC-ColonDB, and EITS, with Dice similarity coefficients of 94.04%, 92.04%, 80.78%, and 76.80%, respectively, and mean intersection over union of 89.31%, 86.81%, 73.55%, and 69.10%, respectively. The simulation experimental results show that the proposed method can effectively segment colon polyp images, providing a new window for the diagnosis of colon polyps.
Humans ; Colonic Polyps/diagnostic imaging* ; Computer Simulation ; Electric Power Supplies ; Semantics ; Image Processing, Computer-Assisted

Based on the top-level ontology and the existing ontology methodology, the related concepts of meridians and acupoints were discriminated, defined and classified; the relationship of core concepts were established, e.g. meridians, acupoints and zangfu. It was attempted to build an ontological semantic framework of meridians and acupoints. Through the investigation on the classification mode of the top-level ontology, it is proposed that the meridians and acupoints, as the unique concepts of traditional Chinese medicine, exist in the form of "emptiness" and belong to "immaterial entity". Meridians refer to the three-dimensional channels in the human body, and acupoints are divided into ontological acupoints and body surface ones. Ontological acupoints are regarded as a three-dimensional structure within the human body, whereas, body surface ones are the optimal sites for acupuncture needle insertion on the body surface, meaning, the zero-dimensional point on the body surface. The main relationships between meridians and acupoints include is-a, exterior-interior, located-in, correspondent-to, mapping, etc. The exploration of the semantic framework of meridians and acupoints is conductive to understanding the connotation of meridians, acupoints and their relationship.
Acupuncture ; Acupuncture Points ; Acupuncture Therapy/methods* ; Humans ; Meridians ; Semantics

The past twenty years have seen the increasingly important role of ontology in traditional Chinese medicine (TCM). However, the development of TCM ontology faces many challenges. Since the epistemologies dramatically differ between TCM and contemporary biomedicine, it is hard to apply the existing top-level ontology mechanically. "Data silos" are widely present in the currently available terminology standards, term sets, and ontologies. The formal representation of ontology needs to be further improved in TCM. Therefore, we propose a unified basic semantic framework of TCM based on in-depth theoretical research on the existing top-level ontology and a re-study of important concepts in TCM. Under such a framework, ontologies in TCM sub-domains should be built collaboratively and be represented formally in a common format. Besides, extensive cooperation should be encouraged by establishing ontology research communities to promote ontology peer review and reuse.
Medicine, Chinese Traditional ; Semantics ; Drugs, Chinese Herbal

Glioma is a primary brain tumor with high incidence rate. High-grade gliomas (HGG) are those with the highest degree of malignancy and the lowest degree of survival. Surgical resection and postoperative adjuvant chemoradiotherapy are often used in clinical treatment, so accurate segmentation of tumor-related areas is of great significance for the treatment of patients. In order to improve the segmentation accuracy of HGG, this paper proposes a multi-modal glioma semantic segmentation network with multi-scale feature extraction and multi-attention fusion mechanism. The main contributions are, (1) Multi-scale residual structures were used to extract features from multi-modal gliomas magnetic resonance imaging (MRI); (2) Two types of attention modules were used for features aggregating in channel and spatial; (3) In order to improve the segmentation performance of the whole network, the branch classifier was constructed using ensemble learning strategy to adjust and correct the classification results of the backbone classifier. The experimental results showed that the Dice coefficient values of the proposed segmentation method in this article were 0.909 7, 0.877 3 and 0.839 6 for whole tumor, tumor core and enhanced tumor respectively, and the segmentation results had good boundary continuity in the three-dimensional direction. Therefore, the proposed semantic segmentation network has good segmentation performance for high-grade gliomas lesions.
Attention ; Glioma/diagnostic imaging* ; Humans ; Magnetic Resonance Imaging/methods* ; Semantics

Ultrasonic examination is a common method in thyroid examination, and the results are mainly composed of thyroid ultrasound images and text reports. Implementation of cross modal retrieval method of images and text reports can provide great convenience for doctors and patients, but currently there is no retrieval method to correlate thyroid ultrasound images with text reports. This paper proposes a cross-modal method based on the deep learning and improved cross-modal generative adversarial network: ①the weight sharing constraints between the fully connection layers used to construct the public representation space in the original network are changed to cosine similarity constraints, so that the network can better learn the common representation of different modal data; ②the fully connection layer is added before the cross-modal discriminator to merge the full connection layer of image and text in the original network with weight sharing. Semantic regularization is realized on the basis of inheriting the advantages of the original network weight sharing. The experimental results show that the mean average precision of cross modal retrieval method for thyroid ultrasound image and text report in this paper can reach 0.508, which is significantly higher than the traditional cross-modal method, providing a new method for cross-modal retrieval of thyroid ultrasound image and text report.
Humans ; Image Processing, Computer-Assisted ; Semantics ; Thyroid Gland

BACKGROUND AND PURPOSE: Semantic memory remains more stable than episodic memory across the lifespan, which makes it potentially useful as a marker for distinguishing pathological aging from normal senescence. To obtain a better understanding of the transitional stage evolving into Alzheimer's dementia (AD), we focused on the amnestic mild cognitive impairment (aMCI) stage stratified based on β-amyloid (Aβ) pathology. METHODS: We analyzed the raw data from Korean version of the Boston Naming Test (K-BNT) and the Controlled Oral Word Association Test (COWAT). For K-BNT, the frequencies of six error types and accuracy rates were evaluated. For a qualitative assessment of the COWAT, we computed the number of switching, number of clusters, and mean cluster size. RESULTS: The data from 217 participants were analyzed (53 normal controls, 66 with Aβ− aMCI, 56 with Aβ+ aMCI, and 42 disease controls). There were fewer semantically related errors and more semantically unrelated errors on the K-BNT in Aβ+ aMCI than in Aβ− aMCI, without a gross difference in the z score. We also found that Aβ+ aMCI showed a more prominent deficit in the number of clusters in the semantic fluency task [especially for animal names (living items)] than Aβ− aMCI. CONCLUSIONS: In spite of similar clinical manifestations, Aβ+ aMCI was more similar to AD than Aβ− aMCI in terms of semantic memory disruption. Semantic memory may serve as an early indicator of brain Aβ pathology. Therefore, semantic memory dysfunction deserves more consideration in clinical practice. Longitudinal research with the follow-up data is needed.
Aging ; Alzheimer Disease ; Animals ; Brain ; Dementia ; Follow-Up Studies ; Humans ; Memory* ; Memory, Episodic ; Mild Cognitive Impairment* ; Pathology ; Semantics* ; Word Association Tests

OBJECTIVES: Suicide is a complex phenomenon not only caused by the individual's mental illness and economic situation, but also occurred in sociocultural contexts and relationships around the individual. Therefore, the attitudes, which include collective norms, thoughts and feelings of a population, toward suicide play a fundamental role in the prevention of suicide. Factor structure of Attitudes Toward Suicide (ATTS), developed by Renberg, is also various in different sociocultural contexts. This is the first study to investigate factor structure of ATTS along with nationwide sample of Korean adults.METHODS: This study analyzed the factor structure and reliability of ATTS in 1500 regionally stratified Korean adults. Exploratory factor analysis was performed by using principal axis factoring and varimax rotation.RESULTS: The selection of 33 ATTS items based on internal consistency and communality was conducted. Five factors were analyzed, which were named ‘Good reason,’ ‘Negative gaze,’ ‘Predictability,’ ‘Means of escape,’ and ‘Common secret,’ respectively. Explained total variance was 41.94%, and the internal consistency ranged from 0.516 to 0.740.CONCLUSIONS: Each of the five factors contains different semantic dimensions. Consistent with previous studies, factors containing permissive attitude toward suicide was high in those with history of suicidal thought and of suicide attempt. It is notable that the ‘Good reason’ showed higher score in elderly. This may be related to socioeconomic or physical adversities which have been considered the major cause of suicide in elderly.
Adult ; Aged ; Factor Analysis, Statistical ; Humans ; Korea ; Semantics ; Suicide

PURPOSE: The aim of this study was to identify core keywords and topic groups of workplace bullying researches in the past 10 years for better understanding research trend.METHODS: The study was conducted in four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building co-occurrence matrix and 4) analyzing network features and clustering topic groups.RESULTS: 437 articles between 2010 and 2019 were retrieved from 5 databases (RISS, NDSL, Google scholar, DBPIA and Kyobo Scholar). Forty-one abstracts from these articles were extracted, and network analysis was conducted using semantic network module. The most important core keywords were ‘turnover’, ‘intention’, ‘factor’, ‘program’ and ‘nursing’. Four topic groups were identified from Korean databases. Major topics were ‘turnover’ and ‘organization culture’.CONCLUSION: After reviewing previous research, it has been found that turnover intention has been emphasized. Further research focused on various intervention is needed to relieve workplace bullying in nursing field.
Bullying ; Data Mining ; Intention ; Korea ; Nursing ; Semantics

BACKGROUND: Eczema is the most common skin problem among children in Hong Kong. Previous studies have highlighted that the quality of life of the families of children with eczema influences the effects of eczema interventions. However, the Chinese version of the Family Dermatology Life Quality Index (C-FDLQI), a tool for measuring the quality of life of the families of children with eczema, has not yet been validated. OBJECTIVE: This study examined the psychometric properties of the C-FDLQI among parents and caregivers of children with eczema in Hong Kong. METHODS: This study evaluated the internal consistency, test-retest reliability and structural validity of the C-FDLQI and its convergent validity by examining its correlations with the SCORing Atopic Dermatitis (SCORAD) and the Cantonese version of the Children’s Dermatology Life Quality Index (C-CDLQI) among 147 Chinese parents/caregivers of children with varying degrees of eczema.
Asian Continental Ancestry Group ; Caregivers ; Child ; Dermatitis, Atopic ; Dermatology ; Eczema ; Hong Kong ; Humans ; Parents ; Psychometrics ; Quality of Life ; Reproducibility of Results ; Semantics ; Skin

BACKGROUND AND PURPOSE: Semantic verbal fluency test is a neuropsychological assessment that can sensitively detect neuropathological changes. Considering its multifactorial features tapping various cognitive domains such as semantic memory, executive function, and working memory, it is necessary to examine verbal fluency performance in association with underlying cognitive functions. The objective of the current study was to investigate semantic fluency patterns of people with mild cognitive impairment (MCI) based on clustering and switching and their relationship with working memory. METHODS: Twenty-six individuals with MCI and 23 normal elderly adults participated in this study. A semantic verbal fluency test (animal version) was administered and the performance was analyzed using the following measures: number of correct words, cluster size, and number of switches. Scores of digit forward (DF) and backward span tasks were employed as working memory measures. RESULTS: Analyses of variance revealed significant group differences in the numbers of correct words and switches. Multivariate logistic regression and receiver-operating characteristic analyses showed that the number of switches more sensitively distinguished MCI existence than the number of correct words. Stepwise linear regression analysis showed that DF task and age significantly predicted the number of correct words while only the DF task significantly predicted the number of switches. CONCLUSIONS: Decrement in semantic verbal fluency in MCI seems to be associated with impaired switching abilities. Working memory capacity might serve as the underlying cognitive factor related to decreased verbal fluency in MCI.
Adult ; Aged ; Cluster Analysis ; Cognition ; Executive Function ; Humans ; Linear Models ; Logistic Models ; Memory ; Memory, Short-Term ; Mild Cognitive Impairment ; Semantics