Displaying all 7 publications

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  1. Jing W
    J Dermatol, 2000 Apr;27(4):225-32.
    PMID: 10824485
    A retrospective analysis of 182 HIV positive Malaysians was done in two centers, the University Hospital Kuala Lumpur (UHKL) and the General Hospital Kuala Lumpur (GHKL) from March 1997 to February 1998. Demographic and clinical data were analyzed. The analysis showed that 130 out of 182 patients had mucocutaneous disorders (71.4%). In the study there were 125 males (96.2%) and 5 females (3.8%). The majority of the patients were in the age group from 20 to 50 years. The patients who presented with mucocutaneous disease also had low CD4+ T lymphocyte counts, and most of them had AIDS defining illnesses. The number of cases with generalized hyperpigmentation was very high (35.7%), followed by papular eruptions (29.1%) and xerosis (27.5%). Seborrheic dermatitis was seen in 19.2% of the cases and psoriasis in 7.7%. The most common infections were oral candida 35.7%, tinea corporis and onychomycosis 9.9%, and herpes infection 4.3%. However, mucocutaneous manifestations of Kaposi's sarcoma were rare. The results suggested that mucocutaneous findings are useful clinical predictors of HIV infection or a sign of the presence of advanced HIV infection.
  2. Jing W, Ismail R
    Int J Dermatol, 1999 Jun;38(6):457-63.
    PMID: 10397587
    BACKGROUND: Mucocutaneous lesions directly related to human immunodeficiency virus (HIV) infection usually present as initial manifestations of immune deficiency. The most common mucocutaneous lesions are Kaposi's sarcoma, histoplasmosis, oro-esophageal candidiasis, oral hairy leukoplakia, and, in Asia, Penicillium marneffei infection. Non-HIV-related skin lesions, such as psoriasis, seborrheic dermatitis, and nodular prurigo, may be the initial presentation among HIV infected patients attending outpatient clinics.

    METHODS: A retrospective analysis was performed on 145 HIV-positive Malaysians of Chinese descent from two centers at the University Hospital Kuala Lumpur (UHKL) and the General Hospital Kuala Lumpur (GHKL) from March 1997 to February 1998. Demographic data and clinical data were analyzed.

    RESULTS: The analysis showed that 104 out of 145 patients had mucocutaneous disorders (71.7%). In the study, there were 100 men (96.2%) and four women (3.8%). The majority of patients were in the age group 20-50 years. The patients who presented with mucocutaneous disease also had low CD4+ T-lymphocyte counts and most had acquired immunodeficiency syndrome (AIDS) defining illness. The number of cases with generalized hyperpigmentation was very high in the group (35.9%), followed by nodular prurigo (29.7%) and xerosis (27.6%). Seborrheic dermatitis was seen in 20.7% of cases, with psoriasis in 8.3%. The most common infections were oral candidiasis (35.9%), tinea corporis and onychomycosis (9.7%), and herpes infection (5.5%); however, mucocutaneous manifestations of Kaposi's sarcoma were rare.

    CONCLUSIONS: The results suggest that mucocutaneous findings are useful clinical predictors of HIV infection or signs of the presence of advanced HIV infection.

  3. Jingya B, Ye H, Jing W, Xi H, Tao H
    ScientificWorldJournal, 2013;2013:180863.
    PMID: 24453807 DOI: 10.1155/2013/180863
    To fully analyze and compare BMI among Han, Tibetan, and Uygur university students, to discuss the differences in their physical properties and physical health, and thus to provide some theoretical suggestions for the improvement of students' physical health.
  4. Jing W, Tao H, Rahman MA, Kabir MN, Yafeng L, Zhang R, et al.
    Work, 2021;68(3):923-934.
    PMID: 33612534 DOI: 10.3233/WOR-203426
    BACKGROUND: Human-Computer Interaction (HCI) is incorporated with a variety of applications for input processing and response actions. Facial recognition systems in workplaces and security systems help to improve the detection and classification of humans based on the vision experienced by the input system.

    OBJECTIVES: In this manuscript, the Robotic Facial Recognition System using the Compound Classifier (RERS-CC) is introduced to improve the recognition rate of human faces. The process is differentiated into classification, detection, and recognition phases that employ principal component analysis based learning. In this learning process, the errors in image processing based on the extracted different features are used for error classification and accuracy improvements.

    RESULTS: The performance of the proposed RERS-CC is validated experimentally using the input image dataset in MATLAB tool. The performance results show that the proposed method improves detection and recognition accuracy with fewer errors and processing time.

    CONCLUSION: The input image is processed with the knowledge of the features and errors that are observed with different orientations and time instances. With the help of matching dataset and the similarity index verification, the proposed method identifies precise human face with augmented true positives and recognition rate.

  5. Zhang G, Jing W, Tao H, Rahman MA, Salih SQ, Al-Saffar A, et al.
    Work, 2021;68(3):935-943.
    PMID: 33612535 DOI: 10.3233/WOR-203427
    BACKGROUND: Human-Robot Interaction (HRI) has become a prominent solution to improve the robustness of real-time service provisioning through assisted functions for day-to-day activities. The application of the robotic system in security services helps to improve the precision of event detection and environmental monitoring with ease.

    OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.

    RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.

    CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.

  6. Tao H, Rahman MA, Jing W, Li Y, Li J, Al-Saffar A, et al.
    Work, 2021;68(3):903-912.
    PMID: 33720867 DOI: 10.3233/WOR-203424
    BACKGROUND: Human-robot interaction (HRI) is becoming a current research field for providing granular real-time applications and services through physical observation. Robotic systems are designed to handle the roles of humans and assist them through intrinsic sensing and commutative interactions. These systems handle inputs from multiple sources, process them, and deliver reliable responses to the users without delay. Input analysis and processing is the prime concern for the robotic systems to understand and resolve the queries of the users.

    OBJECTIVES: In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection.

    RESULTS: The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs.

    CONCLUSION: The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses.

  7. Tu A, Zhu X, Dastjerdi PZ, Yin Y, Peng M, Zheng D, et al.
    Heliyon, 2024 Feb 15;10(3):e24437.
    PMID: 38322894 DOI: 10.1016/j.heliyon.2024.e24437
    BACKGROUND: Traditional Chinese Medicine (TCM), has been used for hepatocellular carcinoma (HCC) at every therapeutic stage, even before tumor formation. However, the efficacy of TCM in reducing the incidence of HCC in patients with chronic hepatitis B-related cirrhosis remains unclear. This study aims to address this gap.

    METHODS: Publications were collected from PubMed, EMBASE, Cochrane Library, Web of Science, CNKI, Sino Med, VIP, and Wan Fang Databases. Relative risk (RR) was calculated with a 95 % confidence interval (CI). Heterogeneity was assessed. The Cochrane Collaboration's tool was used to assess the risk of bias.

    RESULTS: 10 studies with 2702 patients showed that the combination therapy significantly reduced the incidence of HCC in patients with post-hepatitis B cirrhosis at 1, 3, and 5 years. However, the preventive effects of TCM were in compensated cirrhosis, but not the decompensated cirrhosis. Furthermore, TCM correlated with improved liver function and enhanced virological response.

    CONCLUSION: Combination therapy with TCM demonstrated the certain potential in reducing the incidence of HCC in patients with hepatitis B cirrhosis. This is attrinuted to the improvement of liver function and enhancement of the viral response. However, the efficacy of TCM in the field still needs more high-quality RCTs to provide stronger evidence in the future.

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