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Article ; Online: FedOSS: Federated Open Set Recognition via Inter-Client Discrepancy and Collaboration.

Zhu, Meilu / Liao, Jing / Liu, Jun / Yuan, Yixuan

2024 Volume 43, Issue 1, Page(s) 190–202

Abstract: Open set recognition (OSR) aims to accurately classify known diseases and recognize unseen diseases as the unknown class in medical scenarios. However, in existing OSR approaches, gathering data from distributed sites to construct large-scale centralized ...

Abstract	Open set recognition (OSR) aims to accurately classify known diseases and recognize unseen diseases as the unknown class in medical scenarios. However, in existing OSR approaches, gathering data from distributed sites to construct large-scale centralized training datasets usually leads to high privacy and security risk, which could be alleviated elegantly via the popular cross-site training paradigm, federated learning (FL). To this end, we represent the first effort to formulate federated open set recognition (FedOSR), and meanwhile propose a novel Federated Open Set Synthesis (FedOSS) framework to address the core challenge of FedOSR: the unavailability of unknown samples for all anticipated clients during the training phase. The proposed FedOSS framework mainly leverages two modules, i.e., Discrete Unknown Sample Synthesis (DUSS) and Federated Open Space Sampling (FOSS), to generate virtual unknown samples for learning decision boundaries between known and unknown classes. Specifically, DUSS exploits inter-client knowledge inconsistency to recognize known samples near decision boundaries and then pushes them beyond decision boundaries to synthesize discrete virtual unknown samples. FOSS unites these generated unknown samples from different clients to estimate the class-conditional distributions of open data space near decision boundaries and further samples open data, thereby improving the diversity of virtual unknown samples. Additionally, we conduct comprehensive ablation experiments to verify the effectiveness of DUSS and FOSS. FedOSS shows superior performance on public medical datasets in comparison with state-of-the-art approaches. The source code is available at https://github.com/CityU-AIM-Group/FedOSS.
MeSH term(s)	Humans ; Software ; Machine Learning ; Disease
Language	English
Publishing date	2024-01-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	622531-7
ISSN	1558-254X ; 0278-0062
ISSN (online)	1558-254X
ISSN	0278-0062
DOI	10.1109/TMI.2023.3294014
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: 3D Question Answering.

Ye, Shuquan / Chen, Dongdong / Han, Songfang / Liao, Jing

IEEE transactions on visualization and computer graphics

2024 Volume 30, Issue 3, Page(s) 1772–1786

Abstract: Visual question answering (VQA) has experienced tremendous progress in recent years. However, most efforts have only focused on 2D image question-answering tasks. In this article, we extend VQA to its 3D counterpart, 3D question answering (3DQA), which ... ...

Abstract	Visual question answering (VQA) has experienced tremendous progress in recent years. However, most efforts have only focused on 2D image question-answering tasks. In this article, we extend VQA to its 3D counterpart, 3D question answering (3DQA), which can facilitate a machine's perception of 3D real-world scenarios. Unlike 2D image VQA, 3DQA takes the color point cloud as input and requires both appearance and 3D geometrical comprehension to answer the 3D-related questions. To this end, we propose a novel transformer-based 3DQA framework "3DQA-TR", which consists of two encoders to exploit the appearance and geometry information, respectively. Finally, the multi-modal information about the appearance, geometry, and linguistic question can attend to each other via a 3D-linguistic Bert to predict the target answers. To verify the effectiveness of our proposed 3DQA framework, we further develop the first 3DQA dataset "ScanQA", which builds on the ScanNet dataset and contains over 10 K question-answer pairs for 806 scenes. To the best of our knowledge, ScanQA is the first large-scale dataset with natural-language questions and free-form answers in 3D environments that is fully human-annotated. We also use several visualizations and experiments to investigate the astonishing diversity of the collected questions and the significant differences between this task from 2D VQA and 3D captioning. Extensive experiments on this dataset demonstrate the obvious superiority of our proposed 3DQA framework over state-of-the-art VQA frameworks and the effectiveness of our major designs. Our code and dataset will be made publicly available to facilitate research in this direction. The code and data are available at http://shuquanye.com/3DQA_website/.
Language	English
Publishing date	2024-01-30
Publishing country	United States
Document type	Journal Article
ISSN	1941-0506
ISSN (online)	1941-0506
DOI	10.1109/TVCG.2022.3225327
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: A Review of Chloride Penetration of Recycled Concrete with Enhancement Treatment and Service Life Prediction.

Wang, Yuanzhan / Liao, Jing / Zhang, Baohua

Materials (Basel, Switzerland)

2024 Volume 17, Issue 6

Abstract: The application of recycled coarse aggregate (RA) in structural concrete can save non-renewable resources and reduce land occupation. Developing comprehensive knowledge of chloride penetration and service life modeling of recycled coarse aggregate ... ...

Abstract	The application of recycled coarse aggregate (RA) in structural concrete can save non-renewable resources and reduce land occupation. Developing comprehensive knowledge of chloride penetration and service life modeling of recycled coarse aggregate concrete (RAC) is a prerequisite for practice. However, compared with the natural aggregate concrete (NAC), the inferior durability performance, especially chloride penetration resistance, of RAC hinders its application in structural concrete. Therefore, many RAC performance enhancement methods have been proposed. This paper presents a holistic review focused on the chloride penetration of RAC with/without enhancement methods and service life prediction. The current RAC performance enhancement methods are introduced. The improvement effect of the corresponding enhancement methods on the chloride penetration resistance of RAC are discussed and analyzed in turn. Based on the reviewed data on the chloride diffusion coefficient, the modification efficiencies of assorted enhancement methods are summarized. With the hope of promoting RAC application in structural concrete, the current literature on chloride-ingress-based service life prediction for RAC is also overviewed. In addition, the typical influencing factors on chloride transport properties are also discussed, i.e., RA quality. It can be concluded that enhancement techniques can effectively improve the chloride penetration resistance of RAC. The old mortar enhancement or removal methods can improve the chloride penetration resistance by 15-30%, depending on the specific treatment measures. The modification efficiency of the modifier material depends on the specific type and content of the incorporated substance, which ranges from approximately 5% to 95%. The estimated service life of RAC structures decreases with the increasing RA replacement ratio. Finally, concluding remarks are provided concerning future research on the chloride transport behavior of RAC.
Language	English
Publishing date	2024-03-15
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2487261-1
ISSN	1996-1944
ISSN	1996-1944
DOI	10.3390/ma17061349
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Preparation, Characterization and Gelation of a Fungal Nano Chitin Derived from

Liao, Jing / Huang, Huihua

Polymers

2022 Volume 14, Issue 3

Abstract: Nano chitin is a promising biocompatible material with wide applications. In this work, a fungal-derived nano chitin was prepared ... ...

Abstract	Nano chitin is a promising biocompatible material with wide applications. In this work, a fungal-derived nano chitin was prepared from
Language	English
Publishing date	2022-01-25
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym14030474
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Social support, social strain and declines in verbal memory: sex-specific associations based on 16-year follow-up of the English Longitudinal Study of Ageing cohort.

Scholes, Shaun / Liao, Jing

Aging & mental health

2022 Volume 27, Issue 4, Page(s) 780–788

Abstract: Objectives: Previous investigations of cognitive aging have mainly focused on structural aspects of social relations (e.g. network size and composition), thereby neglecting the role of qualitative aspects of social relations. The current longitudinal ... ...

Abstract	Objectives: Previous investigations of cognitive aging have mainly focused on structural aspects of social relations (e.g. network size and composition), thereby neglecting the role of qualitative aspects of social relations. The current longitudinal study examined sex-specific differences in verbal memory decline by measures of perceived relationship quality (social support/strain) by relationship type. Method: In the English Longitudinal Study of Ageing (ELSA), 10,109 participants aged 50-89 years were assessed at wave 1 (baseline: 2002-03) and followed to wave 9 (2017-18). Verbal memory was assessed by immediate and delayed word-recall tasks. Social support/strain was measured by relationship type (spouse; children; family; friends). Random effects within-between (REWB) modelling was used to separate between- and within-person effects. We estimated associations between social support/strain and (1) baseline levels of memory (main effects), and (2) rate of decline in memory (interaction with time-since-baseline). Results: Longitudinal associations were most prominent for men, specific to relationship type, and showed between- rather than within-person effects. Among men, higher spousal strain was associated with faster memory decline (β Conclusion: Between-person differences in social support/strain were modestly associated with memory decline, especially among men.
MeSH term(s)	Male ; Female ; Humans ; Longitudinal Studies ; Follow-Up Studies ; Aging/psychology ; Social Support ; Memory Disorders
Language	English
Publishing date	2022-06-23
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1474804-6
ISSN	1364-6915 ; 1360-7863
ISSN (online)	1364-6915
ISSN	1360-7863
DOI	10.1080/13607863.2022.2089628
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Zs.A 5081: Show issues

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Article ; Online: Causal relationships between peripheral immune cells and Alzheimer's disease: a two-sample Mendelian randomization study.

Liao, Jing / Zhang, Yongquan / Tang, Zhanhong / Liu, Pinjing / He, Luoyi

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology

2024

Abstract: Objective: Previous research suggests that peripheral immune cells may play a role in the development of Alzheimer's disease (AD). Our study aims to determine if the composition of peripheral immune cells directly contributes to the occurrence of AD.: ...

Abstract	Objective: Previous research suggests that peripheral immune cells may play a role in the development of Alzheimer's disease (AD). Our study aims to determine if the composition of peripheral immune cells directly contributes to the occurrence of AD. Methods: We utilized a two-sample Mendelian randomization (MR) approach to examine the association between peripheral immune cells and AD.The primary analysis method used was the inverse variance weighted (IVW) method, and we also conducted analyses using MR Egger, weighted median, simple mode, and weighted mode methods to ensure the accuracy of the results.Heterogeneity and horizontal pleiotropy were evaluated using Cochran's Q statistics and the MR Egger intercept, respectively. Results: The study found a significant correlation between increased IgD + CD24- AC cells (Odds Ratio [OR] = 1.03, 95% Confidence Interval [CI] = 1.01-1.06, P = 0.0172), increased CD4 + %leukocyte (OR = 1.08, 95% CI = 1.02-1.14, P = 0.0086), and increased CD4 + CD8dim AC cells (OR = 1.06, 95% CI = 1.01-1.11, P = 0.0218), with an increased susceptibility to AD. Conversely, an increase in EM DN (CD4-CD8-) %T cells (OR = 0.95, 95% CI = 0.92-0.99, P = 0.0164) and an increase in DN (CD4-CD8-) AC cells (OR = 0.93, 95% CI = 0.88-0.99, P = 0.0145) were associated with a protective effect against AD. Conclusion: Our findings establish a causal link between peripheral immune cells and AD. This study is the first to examine the relationship between peripheral immune cells and AD using MR, offering valuable insights for early diagnosis and treatment decisions.
Language	English
Publishing date	2024-01-25
Publishing country	Italy
Document type	Journal Article
ZDB-ID	2016546-8
ISSN	1590-3478 ; 1590-1874
ISSN (online)	1590-3478
ISSN	1590-1874
DOI	10.1007/s10072-024-07324-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 1877: Show issues

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Article ; Online: Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields.

Zhang, Jingbo / Li, Xiaoyu / Wan, Ziyu / Wang, Can / Liao, Jing

IEEE transactions on visualization and computer graphics

2024 Volume PP

Abstract: Text-driven 3D scene generation is widely applicable to video gaming, film industry, and metaverse applications that have a large demand for 3D scenes. However, existing text-to-3D generation methods are limited to producing 3D objects with simple ... ...

Abstract	Text-driven 3D scene generation is widely applicable to video gaming, film industry, and metaverse applications that have a large demand for 3D scenes. However, existing text-to-3D generation methods are limited to producing 3D objects with simple geometries and dreamlike styles that lack realism. In this work, we present Text2NeRF, which is able to generate a wide range of 3D scenes with complicated geometric structures and high-fidelity textures purely from a text prompt. To this end, we adopt NeRF as the 3D representation and leverage a pre-trained text-to-image diffusion model to constrain the 3D reconstruction of the NeRF to reflect the scene description. Specifically, we employ the diffusion model to infer the text-related image as the content prior and use a monocular depth estimation method to offer the geometric prior. Both content and geometric priors are utilized to update the NeRF model. To guarantee textured and geometric consistency between different views, we introduce a progressive scene inpainting and updating strategy for novel view synthesis of the scene. Our method requires no additional training data but only a natural language description of the scene as the input. Extensive experiments demonstrate that our Text2NeRF outperforms existing methods in producing photo-realistic, multi-view consistent, and diverse 3D scenes from a variety of natural language prompts. Our code and model will be available upon acceptance.
Language	English
Publishing date	2024-02-05
Publishing country	United States
Document type	Journal Article
ISSN	1941-0506
ISSN (online)	1941-0506
DOI	10.1109/TVCG.2024.3361502
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Factors Impacting One-year Follow-up Visit Adherence after Bariatric Surgery in West China: A Mixed Methods Study.

Liao, Jing / Wen, Yue / Yin, Yiqiong / Qin, Yi / Zhang, Guixiang

Obesity surgery

2024

Abstract: Purpose: Quality follow-up (FU) is crucial after bariatric surgery. However, poor adherence after surgery is prevalent. This research aimed to explore the factors related to FU adherence after bariatric surgery in West China.: Materials and methods: ... ...

Abstract	Purpose: Quality follow-up (FU) is crucial after bariatric surgery. However, poor adherence after surgery is prevalent. This research aimed to explore the factors related to FU adherence after bariatric surgery in West China. Materials and methods: This study used a sequential explanatory mixed-methods research design. Participants (n = 177) were identified from the West China Hospital. Demographic information, disease profile, treatment information, and post-surgery FU information were obtained from the bariatric surgery database of the Division of Gastrointestinal Surgery of the West China Hospital. The survey data were analyzed using logistic regression. Semi-structured interviews with participants (n = 10) who had low adherence were conducted. The recording was transcribed verbatim and entered into qualitative data analysis software. Qualitative data were analyzed using a content analysis approach. Results: Multiple logistic regression revealed that living in Chengdu (OR, 2.308), being employed (OR, 2.532), non-smoking (OR, 2.805), and having less than five years of obesity (OR, 2.480) were positive predictors of FU adherence within one year. Semi-structured interviews suggested that factors related to adherence to FU were lack of motivation, lack of opportunity, insufficient ability, and beliefs regarding consequences. Conclusion: Factors impacting one-year FU visit adherence after bariatric surgery include not only demographic and disease-related factors but also social and family factors. These results will provide evidence to support healthcare professionals in developing personalized postoperative FU management strategies.
Language	English
Publishing date	2024-04-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	1070827-3
ISSN	1708-0428 ; 0960-8923
ISSN (online)	1708-0428
ISSN	0960-8923
DOI	10.1007/s11695-024-07227-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 3381: Show issues

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Article ; Online: Learning A Single Network for Robust Medical Image Segmentation with Noisy Labels.

Ye, Shuquan / Xu, Yan / Chen, Dongdong / Han, Songfang / Liao, Jing

IEEE transactions on medical imaging

2024 Volume PP

Abstract: Robust segmenting with noisy labels is an important problem in medical imaging due to the difficulty of acquiring high-quality annotations. Despite the enormous success of recent developments, these developments still require multiple networks to ... ...

Abstract	Robust segmenting with noisy labels is an important problem in medical imaging due to the difficulty of acquiring high-quality annotations. Despite the enormous success of recent developments, these developments still require multiple networks to construct their frameworks and focus on limited application scenarios, which leads to inflexibility in practical applications. They also do not explicitly consider the coarse boundary label problem, which results in sub-optimal results. To overcome these challenges, we propose a novel Simultaneous Edge Alignment and Memory-Assisted Learning (SEAMAL) framework for noisy-label robust segmentation. It achieves single-network robust learning, which is applicable for both 2D and 3D segmentation, in both Set-HQ-knowable and Set-HQ-agnostic scenarios. Specifically, to achieve single-model noise robustness, we design a Memory-assisted Selection and Correction module (MSC) that utilizes predictive history consistency from the Prediction Memory Bank to distinguish between reliable and non-reliable labels pixel-wisely, and that updates the reliable ones at the superpixel level. To overcome the coarse boundary label problem, which is common in practice, and to better utilize shape-relevant information at the boundary, we propose an Edge Detection Branch (EDB) that explicitly learns the boundary via an edge detection layer with only slight additional computational cost, and we improve the sharpness and precision of the boundary with a thinning loss. Extensive experiments verify that SEAMAL outperforms previous works significantly.
Language	English
Publishing date	2024-04-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	622531-7
ISSN	1558-254X ; 0278-0062
ISSN (online)	1558-254X
ISSN	0278-0062
DOI	10.1109/TMI.2024.3389776
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Zs.A 2546: Show issues

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Article ; Online: A bibliometric and visual analysis of research trends and hotspots of familial hypertrophic cardiomyopathy: A review.

Chen, Cong / Liu, Yang / Yang, Songwei / Chen, Ming / Liao, Jing

Medicine

2024 Volume 103, Issue 18, Page(s) e37969

Abstract: Familial hypertrophic cardiomyopathy (FHCM) is an inherited cardiac disease caused by mutations of sarcomere proteins and can be the underlining substrate for major cardiovascular events. Early identification and diagnosis of FHCM are essential to reduce ...

Abstract	Familial hypertrophic cardiomyopathy (FHCM) is an inherited cardiac disease caused by mutations of sarcomere proteins and can be the underlining substrate for major cardiovascular events. Early identification and diagnosis of FHCM are essential to reduce sudden cardiac death. So, this paper summarized the current knowledge on FHCM, and displayed the analysis via bibliometrics method. The relevant literature on FHCM were screened searched via the Web of Science Core Collection database from 2012 to 2022. The literatures were was summarized and analyzed via the bibliometrics method analyzed via CiteSpace and VOSviewer according to topic categories, distribution of spatiotemporal omics and authors, as well as references. Since 2012, there are 909 research articles and reviews related to FHCM. The number of publication for the past 10 years have shown that the development of FHCM research has been steady, with the largest amount of literature in 2012. The most published papers were from the United States, followed by the United Kingdom and Italy. The University of London (63 papers) was the institution that published the most research articles, followed by Harvard University (45 papers) and University College London (45 papers). Keywords formed 3 clusters, focused on the pathogenesis of FHCM, the diagnosis of FHCM, FHCM complications, respectively. The bibliometric analysis and visualization techniques employed herein highlight key trends and focal points in the field, predominantly centered around FHCM's pathogenesis, diagnostic approaches, and its complications. These insights are instrumental in steering future research directions in this area.
MeSH term(s)	Bibliometrics ; Humans ; Cardiomyopathy, Hypertrophic, Familial/genetics ; Biomedical Research/trends
Language	English
Publishing date	2024-05-03
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	80184-7
ISSN	1536-5964 ; 0025-7974
ISSN (online)	1536-5964
ISSN	0025-7974
DOI	10.1097/MD.0000000000037969
Database	MEDical Literature Analysis and Retrieval System OnLINE

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