Title:
DEEP-LEARNING-BASED SIMPLE URINE TEST RESULT TRAINING AND LOWER URINARY TRACT SYMPTOM DIAGNOSIS METHOD
Document Type and Number:
WIPO Patent Application WO/2022/086066
Kind Code:
A1
Abstract:
The present invention relates to simple urine test result training and lower urinary tract symptom diagnosis method and, more specifically, to a simple urine test result training and lower urinary tract symptom diagnosis method which trains a neural network by using simple urine test results that are non-invasive data, and diagnoses lower urinary tract symptoms by using the trained neural network. The present invention provides a lower urinary tract symptom diagnosis method which generates, on the basis of deep learning, a training model by using simple urine test results that are non-invasive data, and diagnoses lower urinary tract symptoms by using the training model, thus preventing a patient from suffering pain and feeling shame during a lower urinary tract symptom diagnosis process and reducing the risk of secondary infection caused by invasive diagnostic methods.
Inventors:
LEE KYU SUNG (KR)
HAN DEOK HYUN (KR)
CHO BAEK HWAN (KR)
BANG SEOK HWAN (KR)
HAN DEOK HYUN (KR)
CHO BAEK HWAN (KR)
BANG SEOK HWAN (KR)
Application Number:
PCT/KR2021/014355
Publication Date:
April 28, 2022
Filing Date:
October 15, 2021
Export Citation:
Assignee:
SAMSUNG LIFE PUBLIC WELFARE FOUNDATION (KR)
International Classes:
A61B5/20; A61B5/00; G06N3/08; G16H50/20
Foreign References:
| JP2007233949A | 2007-09-13 | |||
| KR20200082673A | 2020-07-08 |
Other References:
BANG SEOK HWAN: "A study on the Possibility of Developing a Platform for Predicting Male Lower Urinary Tract Symptoms based on Simple Urinary Tract Examination through Artificial Intelligence Machine Learning", THESIS, GRADUATE SCHOOL OF SUNGKYUNKWAN UNIVERSITY, 28 February 2020 (2020-02-28), XP055924659, Retrieved from the Internet
BAAS S P R: "A machine learning approach to the automatic classification of female uroflowmetry measurements", THESIS, UNIVERSITY OF TWENTE, 25 June 2016 (2016-06-25), XP055924663, Retrieved from the Internet
GIL, D. ; JOHNSSON, M. ; GARCIA CHAMIZO, J.M. ; PAYA, A.S. ; FERNANDEZ, D.R.: "Application of artificial neural networks in the diagnosis of urological dysfunctions", EXPERT SYSTEMS WITH APPLICATIONS, ELSEVIER, AMSTERDAM, NL, vol. 36, no. 3, 1 April 2009 (2009-04-01), AMSTERDAM, NL, pages 5754 - 5760, XP025881343, ISSN: 0957-4174, DOI: 10.1016/j.eswa.2008.06.065
BAAS S P R: "A machine learning approach to the automatic classification of female uroflowmetry measurements", THESIS, UNIVERSITY OF TWENTE, 25 June 2016 (2016-06-25), XP055924663, Retrieved from the Internet
GIL, D. ; JOHNSSON, M. ; GARCIA CHAMIZO, J.M. ; PAYA, A.S. ; FERNANDEZ, D.R.: "Application of artificial neural networks in the diagnosis of urological dysfunctions", EXPERT SYSTEMS WITH APPLICATIONS, ELSEVIER, AMSTERDAM, NL, vol. 36, no. 3, 1 April 2009 (2009-04-01), AMSTERDAM, NL, pages 5754 - 5760, XP025881343, ISSN: 0957-4174, DOI: 10.1016/j.eswa.2008.06.065
Attorney, Agent or Firm:
PCR INTELLECTUAL PROPERTY LAW FIRM (KR)
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