Improving CADx System Performance for Skin Disease Detection using Ensemble Machine Learning Models
Abu Asaduzzaman,
Christian C. Thompson,
Md J. Uddin
Abstract:Conventional computer-aided diagnosis (CADx) systems play a crucial role
in assisting medical professionals with the detection of skin diseases.
However, these systems often involve manual, time-consuming, and
error-prone processes. Recent studies show that machine learning models
have potential to improve the accuracy of CADx systems. In this work, we
present research findings aimed at improving the performance of CADx
systems for detecting skin diseases by applying ensemble machine
learning models. The inves… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.