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  1. Article ; Online: Meaning of non-overlapping patients between the MAFLD and NAFLD definitions.

    Chan, Wah-Kheong / Wong, Vincent W-S

    Liver international : official journal of the International Association for the Study of the Liver

    2022  Volume 42, Issue 2, Page(s) 271–273

    MeSH term(s) Cardiovascular Diseases ; Humans ; Non-alcoholic Fatty Liver Disease/epidemiology
    Language English
    Publishing date 2022-01-28
    Publishing country United States
    Document type Editorial ; Research Support, Non-U.S. Gov't ; Comment
    ZDB-ID 2102783-3
    ISSN 1478-3231 ; 1478-3223
    ISSN (online) 1478-3231
    ISSN 1478-3223
    DOI 10.1111/liv.15142
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  2. Article ; Online: Management of hepatitis B-related cirrhosis in the era of effective antiviral therapy.

    Wong, Vincent W S

    Liver international : official journal of the International Association for the Study of the Liver

    2016  Volume 36, Issue 12, Page(s) 1752–1754

    Language English
    Publishing date 2016-12
    Publishing country United States
    Document type Editorial
    ZDB-ID 2102783-3
    ISSN 1478-3231 ; 1478-3223
    ISSN (online) 1478-3231
    ISSN 1478-3223
    DOI 10.1111/liv.13257
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  3. Book ; Online: Rate-Splitting for Intelligent Reflecting Surface-Aided Multiuser VR Streaming

    Huang, Rui / Wong, Vincent W. S. / Schober, Robert

    2022  

    Abstract: The growing demand for virtual reality (VR) applications requires wireless systems to provide a high transmission rate to support 360-degree video streaming to multiple users simultaneously. In this paper, we propose an intelligent reflecting surface ( ... ...

    Abstract The growing demand for virtual reality (VR) applications requires wireless systems to provide a high transmission rate to support 360-degree video streaming to multiple users simultaneously. In this paper, we propose an intelligent reflecting surface (IRS)-aided rate-splitting (RS) VR streaming system. In the proposed system, RS facilitates the exploitation of the shared interests of the users in VR streaming, and IRS creates additional propagation channels to support the transmission of high-resolution 360-degree videos. IRS also enhances the capability to mitigate the performance bottleneck caused by the requirement that all RS users have to be able to decode the common message. We formulate an optimization problem for maximization of the achievable bitrate of the 360-degree video subject to the quality-of-service (QoS) constraints of the users. We propose a deep deterministic policy gradient with imitation learning (Deep-GRAIL) algorithm, in which we leverage deep reinforcement learning (DRL) and the hidden convexity of the formulated problem to optimize the IRS phase shifts, RS parameters, beamforming vectors, and bitrate selection of the 360-degree video tiles. We also propose RavNet, which is a deep neural network customized for the policy learning in our Deep-GRAIL algorithm. Performance evaluation based on a real-world VR streaming dataset shows that the proposed IRS-aided RS VR streaming system outperforms several baseline schemes in terms of system sum-rate, achievable bitrate of the 360-degree videos, and online execution runtime. Our results also reveal the respective performance gains obtained from RS and IRS for improving the QoS in multiuser VR streaming systems.

    Comment: 20 pages, 12 figures. This paper has been submitted to IEEE journal for possible publication
    Keywords Electrical Engineering and Systems Science - Signal Processing
    Subject code 004
    Publishing date 2022-10-21
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Book ; Online: Online Bitrate Selection for Viewport Adaptive 360-Degree Video Streaming

    Tang, Ming / Wong, Vincent W. S.

    2020  

    Abstract: 360-degree video streaming provides users with immersive experience by letting users determine their field-of-views (FoVs) in real time. To enhance the users' quality of experience (QoE) given their limited bandwidth, recent works have proposed a ... ...

    Abstract 360-degree video streaming provides users with immersive experience by letting users determine their field-of-views (FoVs) in real time. To enhance the users' quality of experience (QoE) given their limited bandwidth, recent works have proposed a viewport adaptive 360-degree video streaming model by exploiting the bitrate adaptation in spatial and temporal domains. Under this video streaming model, in this paper, we consider a scenario with a newly generated 360-degree video without viewing history from other users. To maximize the user's QoE, we propose an online bitrate selection algorithm, called OBS360. The proposed online algorithm can adapt to the unknown and heterogeneous users' FoVs and downloading capacities. We prove that the proposed algorithm achieves sublinear dynamic regret under a convex decision set. This suggests that as the number of video segments increases, the performance of the online algorithm approaches the performance of the offline algorithm, where the users' FoVs and downloading capacities are known. We perform simulations with real-world dataset to evaluate the performance of the proposed algorithm. Results show that compared with several existing methods, our proposed algorithm can enhance the users' QoE significantly by improving the viewing bitrate and reducing the inter-segment and intra-segment degradation losses of the users.
    Keywords Computer Science - Networking and Internet Architecture
    Subject code 005
    Publishing date 2020-04-10
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Book ; Online: Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing Systems

    Tang, Ming / Wong, Vincent W. S.

    2020  

    Abstract: In mobile edge computing systems, an edge node may have a high load when a large number of mobile devices offload their tasks to it. Those offloaded tasks may experience large processing delay or even be dropped when their deadlines expire. Due to the ... ...

    Abstract In mobile edge computing systems, an edge node may have a high load when a large number of mobile devices offload their tasks to it. Those offloaded tasks may experience large processing delay or even be dropped when their deadlines expire. Due to the uncertain load dynamics at the edge nodes, it is challenging for each device to determine its offloading decision (i.e., whether to offload or not, and which edge node it should offload its task to) in a decentralized manner. In this work, we consider non-divisible and delay-sensitive tasks as well as edge load dynamics, and formulate a task offloading problem to minimize the expected long-term cost. We propose a model-free deep reinforcement learning-based distributed algorithm, where each device can determine its offloading decision without knowing the task models and offloading decision of other devices. To improve the estimation of the long-term cost in the algorithm, we incorporate the long short-term memory (LSTM), dueling deep Q-network (DQN), and double-DQN techniques. Simulation results with 50 mobile devices and five edge nodes show that the proposed algorithm can reduce the ratio of dropped tasks and average task delay by 86.4%-95.4% and 18.0%-30.1%, respectively, when compared with several existing algorithms.
    Keywords Computer Science - Networking and Internet Architecture
    Subject code 000 ; 006
    Publishing date 2020-04-10
    Publishing country us
    Document type Book ; Online
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  6. Book ; Online: Joint User Pairing and Association for Multicell NOMA

    Ma, Manyou / Wong, Vincent W. S.

    A Pointer Network-based Approach

    2020  

    Abstract: In this paper, we investigate the joint user pairing and association problem for multicell non-orthogonal multiple access (NOMA) systems. We consider a scenario where the user equipments (UEs) are located in a multicell network equipped with multiple ... ...

    Abstract In this paper, we investigate the joint user pairing and association problem for multicell non-orthogonal multiple access (NOMA) systems. We consider a scenario where the user equipments (UEs) are located in a multicell network equipped with multiple base stations. Each base station has multiple orthogonal physical resource blocks (PRBs). Each PRB can be allocated to a pair of UEs using NOMA. Each UE has the additional freedom to be served by any one of the base stations, which further increases the complexity of the joint user pairing and association algorithm design. Leveraging the recent success on using machine learning to solve numerical optimization problems, we formulate the joint user pairing and association problem as a combinatorial optimization problem. The solution is found using an emerging deep learning architecture called Pointer Network (PtrNet), which has a lower computational complexity compared to solutions based on iterative algorithms and has been proven to achieve near-optimal performance. The training phase of the PtrNet is based on deep reinforcement learning (DRL), and does not require the use of the optimal solution of the formulated problem as training labels. Simulation results show that the proposed joint user pairing and association scheme achieves near-optimal performance in terms of the aggregate data rate, and outperforms the random user pairing and association heuristic by up to 30%.

    Comment: accepted for publication in Proc. of 6th International Workshop on NOMA for 5G and Beyond, co-located with IEEE International Conference on Communications (ICC), Dublin, Ireland, Jun. 2020
    Keywords Computer Science - Information Theory ; Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Signal Processing ; Statistics - Machine Learning
    Subject code 006
    Publishing date 2020-04-15
    Publishing country us
    Document type Book ; Online
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  7. Article ; Online: Performance of continuous controlled attenuation parameter and liver stiffness measurement by the novel SmartExam in metabolic dysfunction-associated steatotic liver disease.

    Song, Sherlot J / Nogami, Asako / Liang, Lilian Y / Yoneda, Masato / Leung, Howard H W / Nakajima, Atsushi / Lai, Jimmy C T / Wong, Grace L H / Shu, Sally S T / Wong, Vincent W S / Yip, Terry C F

    Liver international : official journal of the International Association for the Study of the Liver

    2024  Volume 44, Issue 5, Page(s) 1167–1175

    Abstract: Background & aims: FibroScan® Expert 630 and FibroScan® Mini+430 are novel vibration-controlled transient elastography devices equipped with the same SmartExam software, which allows continuous measurement of controlled attenuation parameter (CAP) ... ...

    Abstract Background & aims: FibroScan® Expert 630 and FibroScan® Mini+430 are novel vibration-controlled transient elastography devices equipped with the same SmartExam software, which allows continuous measurement of controlled attenuation parameter (CAP) during the entire examination. This study aims to compare the CAP variabilities and the quantification for liver fibrosis and steatosis between the conventional FibroScan and the SmartExam-equipped machines in patients with metabolic dysfunction-associated steatotic liver disease (MASLD).
    Methods: This retrospective study included 118 patients with biopsy-proven MASLD who underwent liver biopsy at two tertiary centres between 2021 and 2023. Liver stiffness and steatosis measurements were performed using both FibroScan machines and M and XL probes for each individual. Liver histology was used as the reference standard for liver fibrosis and steatosis staging.
    Results: Standard deviations of continuous CAP (cCAP) were significantly lower than those of CAP for all probes (p < .0001). CAP variability was significantly associated with body mass index (p < .01), probe selection (p < .001) as well as the random effect of centre. Only the effect of probe selection (p < .001) was significantly associated with cCAP variability. No significant difference was found in the performance of staging liver fibrosis and steatosis between two types of machines at the same cut-offs.
    Conclusions: The SmartExam-based VCTE reduces the variability of CAP measurement and achieves a similar accuracy as the FibroScan 502 device for the estimation of both hepatic steatosis and fibrosis. Future studies should determine if cCAP is a better tool to monitor changes in steatosis than the original CAP.
    MeSH term(s) Humans ; Elasticity Imaging Techniques ; Non-alcoholic Fatty Liver Disease/pathology ; Retrospective Studies ; Liver/pathology ; Liver Cirrhosis/pathology ; Metabolic Diseases
    Language English
    Publishing date 2024-02-14
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2102783-3
    ISSN 1478-3231 ; 1478-3223
    ISSN (online) 1478-3231
    ISSN 1478-3223
    DOI 10.1111/liv.15862
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  8. Article ; Online: Fibroblast growth factor 21 for non-alcoholic steatohepatitis.

    Wong, Vincent W S / Adams, Leon A

    Lancet (London, England)

    2018  Volume 392, Issue 10165, Page(s) 2658–2660

    MeSH term(s) Double-Blind Method ; Fibroblast Growth Factors ; Humans ; Non-alcoholic Fatty Liver Disease
    Chemical Substances fibroblast growth factor 21 ; Fibroblast Growth Factors (62031-54-3)
    Language English
    Publishing date 2018-12-13
    Publishing country England
    Document type Journal Article ; Comment
    ZDB-ID 3306-6
    ISSN 1474-547X ; 0023-7507 ; 0140-6736
    ISSN (online) 1474-547X
    ISSN 0023-7507 ; 0140-6736
    DOI 10.1016/S0140-6736(18)32165-2
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  9. Article ; Online: Management of NAFLD in primary care settings.

    Wong, Vincent W S / Zelber-Sagi, Shira / Cusi, Kenneth / Carrieri, Patrizia / Wright, Eugene / Crespo, Javier / Lazarus, Jeffrey V

    Liver international : official journal of the International Association for the Study of the Liver

    2022  Volume 42, Issue 11, Page(s) 2377–2389

    Abstract: Non-alcoholic fatty liver disease (NAFLD) affects at least 25% of the general population and is an increasingly important cause of cirrhosis and hepatocellular carcinoma. Although it is the research focus of the hepatology field, it is clear that primary ...

    Abstract Non-alcoholic fatty liver disease (NAFLD) affects at least 25% of the general population and is an increasingly important cause of cirrhosis and hepatocellular carcinoma. Although it is the research focus of the hepatology field, it is clear that primary care physicians are seeing the majority of NAFLD patients and are in a pivotal position to provide quality care. In this article, we review the role of primary care in the management of NAFLD. NAFLD is common in patients with diabetes, obesity and other metabolic risk factors. Abdominal ultrasonography is the most commonly used method to diagnose fatty liver. Simple fibrosis scores have high negative predictive values in excluding advanced liver fibrosis and future liver-related events and can be used in primary care as initial evaluation. An abnormal result should be followed by subsequent workup or specialist referral. Primary care is the ideal setting to institute multidisciplinary care, especially the involvement of dietitians and physical activity trainers in lifestyle intervention, as well as initiating the discussion of bariatric surgery in patients with severe obesity. Although specific drug treatment for steatohepatitis would require a more precise diagnosis, metabolic drugs that improve both steatohepatitis and cardiovascular outcomes (e.g. glucagon-like peptide-1 receptor agonists) may be considered in patients with NAFLD.
    MeSH term(s) Glucagon-Like Peptide-1 Receptor/therapeutic use ; Humans ; Liver Cirrhosis/diagnosis ; Non-alcoholic Fatty Liver Disease/complications ; Non-alcoholic Fatty Liver Disease/diagnosis ; Non-alcoholic Fatty Liver Disease/therapy ; Primary Health Care
    Chemical Substances Glucagon-Like Peptide-1 Receptor
    Language English
    Publishing date 2022-09-01
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2102783-3
    ISSN 1478-3231 ; 1478-3223
    ISSN (online) 1478-3231
    ISSN 1478-3223
    DOI 10.1111/liv.15404
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  10. Article ; Online: Dynamic Glucose-Enhanced Imaging of the Liver Using Breath-Hold Black Blood Quantitative T

    Qian, Yurui / Wong, Vincent W S / Wang, Yi-Xiang / Hou, Jian / Jiang, Baiyan / Zhang, Xinrong / Wong, Grace L H / Chan, Queenie / Yu, Simon C H / Chu, Winnie C W / Chen, Weitian

    Journal of magnetic resonance imaging : JMRI

    2023  Volume 59, Issue 3, Page(s) 1107–1109

    MeSH term(s) Humans ; Glucose ; Magnetic Resonance Imaging/methods ; Liver ; Breath Holding
    Chemical Substances Glucose (IY9XDZ35W2)
    Language English
    Publishing date 2023-06-14
    Publishing country United States
    Document type Letter
    ZDB-ID 1146614-5
    ISSN 1522-2586 ; 1053-1807
    ISSN (online) 1522-2586
    ISSN 1053-1807
    DOI 10.1002/jmri.28829
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