The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Feb. 20, 2024
Filed:
Sep. 27, 2022
Taichung Veterans General Hospital, Taichung, TW;
Tunghai University, Taichung, TW;
Ming-Cheng Chan, Taichung, TW;
Kai-Chih Pai, Taichung, TW;
Wen-Cheng Chao, Taichung, TW;
Yu-Jen Huang, Taichung, TW;
Chieh-Liang Wu, Taichung, TW;
Min-Shian Wang, Taichung, TW;
Chien-Lun Liao, Taichung, TW;
Ta-Chun Hung, Taichung, TW;
Yan-Nan Lin, Taichung, TW;
Hui-Chiao Yang, Taichung, TW;
Ruey-Kai Sheu, Taichung, TW;
Lun-Chi Chen, Taichung, TW;
TAICHUNG VETERANS GENERAL HOSPITAL, Taichung, TW;
TUNGHAI UNIVERSITY, Taichung, TW;
Abstract
A respiratory status classifying method is for classifying as one of at least two respiratory statuses and includes an original physiological parameter inputting step, an original chest image inputting step, a characteristic physiological parameter generating step, a characteristic chest image generating step, a training step and a classifier generating step. The characteristic chest image generating step includes processing at least a part of the original chest images, segmenting images of a left lung, a right lung and a heart from each of the original chest images that are processed, and enhancing image data of the images being segmented, so as to generate a plurality of characteristic chest images. The training step includes training two respiratory status classifiers using a plurality of characteristic physiological parameters and the characteristic chest images by at least one machine learning algorithm.