An integrative latent class model of heterogeneous data modalities for diagnosing kidney obstruction.

ABSTRACT: Radionuclide imaging plays a critical role in the diagnosis and management of kidney obstruction. However, most practicing radiologists in US hospitals have insufficient time and resources to acquire training and experience needed to interpret radionuclide images, leading to increased diagnostic errors. To tackle this problem, Emory University embarked on a study that aims to develop a computer-assisted diagnostic (CAD) tool for kidney obstruction by mining and analyzing patient data comprised of renogram curves, ordinal expert ratings on the obstruction status, pharmacokinetic variables, and demographic information. The major challenges here are the heterogeneity in data modes and the lack of gold standard for determining kidney obstruction. In this article, we develop a statistically pri

SUBMITTER: Jang JH 

PROVIDER: S-EPMC11247177 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature