Patents by Inventor Xiuchuan TANG

Xiuchuan TANG has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12346778
    Abstract: The disclosure discloses an AI-based condition classification system for patients with novel coronavirus, which includes: a classification model acquisition module for training one or more binary classification models that classify patient conditions according to patient data, and obtain the most accurate binary classification model as the target model, and determine the interpretable features in the patient data; a preprocessing module is configured to extract the interpretable features in the patient data to be classified, and then perform preprocessing on the extracted features to fill in the missing values and replace the abnormal values in the data, so as to obtain the features to be classified after the preprocessing is completed; a condition classification module is configured to use the features to be classified as the input for the target model, and the target model is used to complete condition classification for the patients to be classified.
    Type: Grant
    Filed: July 29, 2020
    Date of Patent: July 1, 2025
    Assignee: HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY
    Inventors: Ye Yuan, Chuan Sun, Li Yan, Hui Xu, Maolin Wang, Yuqi Guo, Xiuchuan Tang, Haitao Zhang, Yang Xiao
  • Publication number: 20220122739
    Abstract: The disclosure discloses an AI-based condition classification system for patients with novel coronavirus, which includes: a classification model acquisition module for training one or more binary classification models that classify patient conditions according to patient data, and obtain the most accurate binary classification model as the target model, and determine the interpretable features in the patient data; a preprocessing module is configured to extract the interpretable features in the patient data to be classified, and then perform preprocessing on the extracted features to fill in the missing values and replace the abnormal values in the data, so as to obtain the features to be classified after the preprocessing is completed; a condition classification module is configured to use the features to be classified as the input for the target model, and the target model is used to complete condition classification for the patients to be classified.
    Type: Application
    Filed: July 29, 2020
    Publication date: April 21, 2022
    Applicant: HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY
    Inventors: Ye YUAN, Chuan SUN, Li YAN, Hui XU, Maolin WANG, Yuqi GUO, Xiuchuan TANG, Haitao ZHANG, Yang XIAO