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5. Using Information Technology to Manage the COVID-19 Pandemic: Development of a Technical Framework Based on Practical Experience in China

Author

Ye, Qing, Zhou, Jin, and Wu, Hong

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

BackgroundThe coronavirus disease (COVID-19) epidemic poses an enormous challenge to the global health system, and governments have taken active preventive and control measures. The health informatics community in China has actively taken action to leverage health information technologies for epidemic monitoring, detection, early warning, prevention and control, and other tasks. ObjectiveThe aim of this study was to develop a technical framework to respond to the COVID-19 epidemic from a health informatics perspective. MethodsIn this study, we collected health information technology–related information to understand the actions taken by the health informatics community in China during the COVID-19 outbreak and developed a health information technology framework for epidemic response based on health information technology–related measures and methods. ResultsBased on the framework, we review specific health information technology practices for managing the outbreak in China, describe the highlights of their application in detail, and discuss critical issues to consider when using health information technology. Technologies employed include mobile and web-based services such as Internet hospitals and Wechat, big data analyses (including digital contact tracing through QR codes or epidemic prediction), cloud computing, Internet of things, Artificial Intelligence (including the use of drones, robots, and intelligent diagnoses), 5G telemedicine, and clinical information systems to facilitate clinical management for COVID-19. ConclusionsPractical experience in China shows that health information technologies play a pivotal role in responding to the COVID-19 epidemic.

Published
2020
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7. How Resource Scarcity and Accessibility Affect Patients’ Usage of Mobile Health in China: Resource Competition Perspective

Author

Ye, Qing, Deng, Zhaohua, Chen, Yanyan, Liao, Jiazhi, Li, Gang, and Lu, Yaobin

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundThe last decade has witnessed many achievements in China’s health care industry, but the industry still faces major challenges among which the uneven distribution of medical resources and the imbalance between supply and demand are the most pressing problems. Although mobile health (mHealth) services play a significant role in mitigating problems associated with health care delivery, their adoption rates have been low. ObjectiveThe objective of this study was to explore the impact of resource scarcity and resource accessibility on the adoption of mHealth from the perspective of resource competition, to examine the concerning factors, and to provide a theoretical basis for promoting mHealth in China. MethodsWe used 229,516 original registration records of outpatients to conduct an empirical analysis to examine the adoption of mHealth services from the perspective of resource competition. ResultsThe adoption rate of mobile services for outpatients was low, accounting for only 31.5% (N=71,707). The empirical results indicated that resource scarcity (beta=.435, P=.01) and accessibility (beta=−.134, P=.02) have a significant impact on the adoption of mHealth. In addition, gender (beta=.073, P=.01) and age (beta=−.009, P

Published
2019
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31. An efficient molecular genetic testing strategy for incontinentia pigmenti based on single-tube long fragment read sequencing

Author

Min Chen, Mei-Hua Tan, Jiao Liu, Yan-Mei Yang, Jia-Ling Yu, Li-Juan He, Ying-Zhi Huang, Yi-Xi Sun, Ye-Qing Qian, Kai Yan, and Min-Yue Dong

Subjects
Medicine, Genetics, QH426-470
Abstract

Abstract Incontinentia pigmenti (IP) is a rare X-linked dominant neuroectodermal dysplasia that primarily affects females. The only known causative gene is IKBKG, and the most common genetic cause is the recurrent IKBKG △4–10 deletion resulting from recombination between two MER67B repeats. Detection of variants in IKBKG is challenging due to the presence of a highly homologous non-pathogenic pseudogene IKBKGP1. In this study, we successfully identified four pathogenic variants in four IP patients using a strategy based on single-tube long fragment read (stLFR) sequencing with a specialized analysis pipeline. Three frameshift variants (c.519-3_519dupCAGG, c.1167dupC, and c.700dupT) were identified and subsequently validated by Sanger sequencing. Notably, c.519-3_519dupCAGG was found in both IKBKG and IKBKGP1, whereas the other two variants were only detected in the functional gene. The IKBKG △4–10 deletion was identified and confirmed in one patient. These results demonstrate that the proposed strategy can identify potential pathogenic variants and distinguish whether they are derived from IKBKG or its pseudogene. Thus, this strategy can be an efficient genetic testing method for IKBKG. By providing a comprehensive understanding of the whole genome, it may also enable the exploration of other genes potentially associated with IP. Furthermore, the strategy may also provide insights into other diseases with detection challenges due to pseudogenes.

Published
2024
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38. Real-world treatment outcome with protease inhibitor direct-acting antiviral in advanced hepatitis C cirrhosis: a REAL-C study

Author

Wong, Yu Jun, Tran, Sally, Huang, Chung-Feng, Hsu, Yao-Chun, Preda, Carmen, Toyoda, Hidenori, Liu, Joanne, Jun, Dae Won, Landis, Charles, Huang, Daniel Q., Gila, Andrei, Negoita, Livia, Yasuda, Satoshi, Tseng, Cheng-Hao, Tsai, Pei-Chien, Uojima, Haruki, Nozaki, Akito, Chuma, Makoto, Atsukawa, Masanori, Ishigami, Masatoshi, Itokawa, Norio, Iio, Etsuko, Lam, Carla Pui-Mei, Watanabe, Tsunamasa, Asai, Akira, Yokohama, Keisuke, Abe, Hiroshi, Enomoto, Masaru, Kawada, Norifumi, Tamori, Akihiro, Lee, Dong Hyun, Jun, Mi Jung, Do, Son, Vo, Dang K. H., Liu, Li, Li, Junyi, Ji, Fanpu, Wang, Wenjun, Li, Yu, Wang, Xiaozhong, Guo, Fen, Xu, Qiang, Jing, Liang, Ye, Qing, Pan, Hongying, Zhang, JiaJie, Wen, Xie, Wang, Qi, Ren, Hong, Cai, Dachuan, Shang, Jia, Liu, Junping, Lu, Chengzheng, Zang, Wenqian, Li, Jia, Niu, Junqi, Zhang, Mingyuan, Wu, Chao, Huang, Rui, Maeda, Mayumi, Nakanishi, Akiko, Yeh, Ming-Lun, Chuang, Wan-Long, Huang, Jee-Fu, Dai, ChiaYen, Ishikawa, Toru, Takaguchi, Koichi, Senoh, Tomonori, Trinh, Huy N., Takahashi, Hirokazu, Eguchi, Yuichiro, Quek, Sabrina Xin Zi, Haga, Hiroaki, Ogawa, Eiichi, Wong, Grace, Buti, Maria, Fukunishi, Shinya, Ueno, Yoshiyuki, Yuen, Man-Fung, Tanaka, Yasuhito, Lim, Seng Gee, Cheung, Ramsey, Yu, Ming-Lung, and Nguyen, Mindie H.

Published
2023
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39. LANA: Towards Personalized Deep Knowledge Tracing through Distinguishable Interactive Sequences

Author

Zhou, Yuhao, Li, Xihua, Cao, Yunbo, Zhao, Xuemin, Ye, Qing, and Lv, Jiancheng

Abstract

In educational applications, "Knowledge Tracing" (KT) has been widely studied for decades as it is considered a fundamental task towards adaptive online learning. Among proposed KT methods, Deep Knowledge Tracing (DKT) and its variants are by far the most effective ones due to the high flexibility of the neural network. However, DKT often ignores the inherent differences between students (e.g. memory skills, reasoning skills, ...), averaging the performances of all students, leading to the lack of personalization, and therefore was considered insufficient for adaptive learning. To alleviate this problem, in this paper, we proposed Leveled Attentive KNowledge TrAcing (LANA), which firstly uses a novel student-related features extractor (SRFE) and pivot modules to distill and distinguish students' unique inherent properties from their respective interactive sequences. Moreover, inspired by Item Response Theory (IRT), the interpretable Rasch model was used to cluster students by their ability levels, and thereby utilizing leveled learning to assign different encoders to different groups of students. With pivot module reconstructed the decoder for individual students and leveled learning specialized encoders for groups, personalized DKT was achieved. Extensive experiments conducted on two real-world large-scale datasets demonstrated that our proposed LANA improves the AUC score by at least 1.00% (i.e. EdNet [up arrow] 1.46% and RAIEd2020 [up arrow] 1.00%), substantially surpassing the other State-Of-The-Art KT methods. [For the full proceedings, see ED615472.]

Published
2021

40. The urinary microbiota composition and functionality of calcium oxalate stone formers

Author

Jing Xie, Xue-qi Zhang, Ji-nan Guo, Qian Yuan, Ke-feng Xiao, and Ye-qing Yuan

Subjects
calcium oxalate stones, functionality, microbiota, shotgun, urine, Microbiology, QR1-502
Abstract

BackgroundAccumulated evidences indicate that dysbiosis of the urinary microbiota is associated with kidney stone formation. In the present study, we aimed to investigate the urinary microbiota composition and functionality of patients with calcium oxalate stones and compare it with those of healthy individuals.MethodWe collected bladder urine samples from 68 adult patients with calcium oxalate stones and 54 age-matched healthy controls by transurethral catheterization. 16S rRNA gene and shotgun sequencing were utilized to characterize the urinary microbiota and functionality associated with calcium oxalate stones.ResultsAfter further exclusion, a total of 100 subjects was finally included and analyzed. The diversity of the urinary microbiota in calcium oxalate stone patients was not significantly different from that of healthy controls. However, the urinary microbiota structure of calcium oxalate stone formers significantly differed from that of healthy controls (PERMANOVA, r = 0.026, P = 0.019). Differential representation of bacteria (e.g., Bifidobacterium) and several enriched functional pathways (e.g., threonine biosynthesis) were identified in the urine of calcium oxalate stone patients.ConclusionOur results showed significantly different urinary microbiota structure and several enriched functional pathways in calcium oxalate stone patients, which provide new insight into the pathogenesis of calcium oxalate stones.

Published
2024
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