Histopathological Gastric Cancer Detection on GasHisSDB Dataset Using Deep Ensemble Learning.

ABSTRACT: Gastric cancer is a leading cause of cancer-related deaths worldwide, underscoring the need for early detection to improve patient survival rates. The current clinical gold standard for detection is histopathological image analysis, but this process is manual, laborious, and time-consuming. As a result, there has been growing interest in developing computer-aided diagnosis to assist pathologists. Deep learning has shown promise in this regard, but each model can only extract a limited number of image features for classification. To overcome this limitation and improve classification performance, this study proposes ensemble models that combine the decisions of several deep learning models. To evaluate the effectiveness of the proposed models, we tested their performance on the publicly ava

SUBMITTER: Yong MP 

PROVIDER: S-EPMC10217020 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature