This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1340) Machine Learning (1401) Machine Learning (52) Computer-Aided Diagnosis (102) Urology (17) Decision Support for Health Professionals (1147) Clinical Information and Decision Making (37)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58599, first published .
Building Dual AI Models and Nomograms Using Noninvasive Parameters for Aiding Male Bladder Outlet Obstruction Diagnosis and Minimizing the Need for Invasive Video-Urodynamic Studies: Development and Validation Study

Building Dual AI Models and Nomograms Using Noninvasive Parameters for Aiding Male Bladder Outlet Obstruction Diagnosis and Minimizing the Need for Invasive Video-Urodynamic Studies: Development and Validation Study

Building Dual AI Models and Nomograms Using Noninvasive Parameters for Aiding Male Bladder Outlet Obstruction Diagnosis and Minimizing the Need for Invasive Video-Urodynamic Studies: Development and Validation Study

Authors of this article:

Chung-You Tsai1, 2 Author Orcid Image ;   Jing-Hui Tian3 Author Orcid Image ;   Chien-Cheng Lee2 Author Orcid Image ;   Hann-Chorng Kuo4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

There are no citations yet available for this article according to Crossref .