• Clinical features and the traditional Chinese medicine therapeutic characteristics of 293 COVID-19 inpatient cases 

      Shu, Zixin; Zhou, Yana; Chang, Kai; Liu, Jifen; Min, Xiaojun; Zhang, Qing; Sun, Jing; Xiong, Yajuan; Zou, Qunsheng; Zheng, Qiguang; Ji, Jinghui; Poon, Josiah; Liu, Baoyan; Zhou, Xuezhong; Li, Xiaodong
      Published 2020
      Coronavirus disease 2019 (COVID-19) is now pandemic worldwide and has heavily overloaded hospitals in Wuhan City, China during the time between late January and February. We reported the clinical features and therapeutic ...
      Article
    • CovidXrayNet: Optimizing data augmentation and CNN hyperparameters for improved COVID-19 detection from CXR 

      Monshi, Maram Mahmoud A; Poon, Josiah; Chung, Vera; Monshi, Fahad Mahmoud
      Published 2021
      To mitigate the spread of the current coronavirus disease 2019 (COVID-19) pandemic, it is crucial to have an effective screening of infected patients to be isolated and treated. Chest X-Ray (CXR) radiological imaging coupled ...
      Article
    • Deep learning in generating radiology reports: A survey 

      Monshi, Maram Mahmoud A.; Poon, Josiah; Chung, Vera
      Published 2020
      Substantial progress has been made towards implementing automated radiology reporting models based on deep learning (DL). This is due to the introduction of large medical text/image datasets. Generating radiology coherent ...
      Article
    • Phenonizer: A Fine-Grained Phenotypic Named Entity Recognizer for Chinese Clinical Texts 

      Zou, Qunsheng; Yang, Kuo; Shu, Zixin; Chang, Kai; Zheng, Qiguang; Zheng, Yi; Lu, Kezhi; Xu, Ning; Tian, Haoyu; Li, Xiaomeng; Yang, Yuxia; Zhou, Yana; Yu, Haibin; Zhang, Xiaoping; Xia, Jianan; Zhu, Qiang; Poon, Josiah; Poon, Simon; Zhang, Runshun; Li, Xiaodong; Zhou, Xuezhong
      Published 2022
      Biomedical named entity recognition (BioNER) from clinical texts is a fundamental task for clinical data analysis due to the availability of large volume of electronic medical record data, which are mostly in free text ...
      Article