Patents by Inventor Tsai-Jung WANG

Tsai-Jung WANG 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).

  • Acute kidney injury predicting system and method thereof
    Patent number: 11937932
    Abstract: An acute kidney injury predicting system and a method thereof are proposed. A processor reads the data to be tested, the detection data, the machine learning algorithm and the risk probability comparison table from a main memory. The processor trains the detection data according to the machine learning algorithm to generate an acute kidney injury prediction model, and inputs the data to be tested into the acute kidney injury prediction model to generate an acute kidney injury characteristic risk probability and a data sequence table. The data sequence table lists the data to be tested in sequence according to a proportion of each of the data to be tested in the acute kidney injury characteristics. The processor selects one of the medical treatment data from the risk probability comparison table according to the acute kidney injury characteristic risk probability.
    Type: Grant
    Filed: July 8, 2022
    Date of Patent: March 26, 2024
    Assignees: TAICHUNG VETERANS GENERAL HOSPITAL, TUNGHAI UNIVERSITY
    Inventors: Chieh-Liang Wu, Chun-Te Huang, Cheng-Hsu Chen, Tsai-Jung Wang, Kai-Chih Pai, Chun-Ming Lai, Min-Shian Wang, Ruey-Kai Sheu, Lun-Chi Chen, Yan-Nan Lin, Chien-Lun Liao, Ta-Chun Hung, Chien-Chung Huang, Chia-Tien Hsu, Shang-Feng Tsai
  • ACUTE KIDNEY INJURY PREDICTING SYSTEM AND METHOD THEREOF
    Publication number: 20230380742
    Abstract: An acute kidney injury predicting system and a method thereof are proposed. A processor reads the data to be tested, the detection data, the machine learning algorithm and the risk probability comparison table from a main memory. The processor trains the detection data according to the machine learning algorithm to generate an acute kidney injury prediction model, and inputs the data to be tested into the acute kidney injury prediction model to generate an acute kidney injury characteristic risk probability and a data sequence table. The data sequence table lists the data to be tested in sequence according to a proportion of each of the data to be tested in the acute kidney injury characteristics. The processor selects one of the medical treatment data from the risk probability comparison table according to the acute kidney injury characteristic risk probability.
    Type: Application
    Filed: July 8, 2022
    Publication date: November 30, 2023
    Inventors: Chun-Te HUANG, Kai-Chih PAI, Tsai-Jung WANG, Min-Shian WANG, Yan-Nan LIN, Cheng-Hsu CHEN, Chun-Ming LAI, Ruey-Kai SHEU, Lun-Chi CHEN, Chieh-Liang WU, Chien-Lun LIAO, Ta-Chun HUNG, Chien-Chung HUANG, Chia-Tien HSU, Shang-Feng TSAI