Presentation information

General Session

General Session » GS-10 AI application

[3F1-GS-10i] AI応用:医療情報

Thu. Jun 10, 2021 9:00 AM - 10:40 AM Room F (GS room 1)

座長:石畠 正和(NTT)

9:20 AM - 9:40 AM

[3F1-GS-10i-02] Deep learning for diagnosis of cardiac disease from a small dataset of echocardiogram videos

〇Mitsuhiko Nakamoto1, Susumu Katsushika1, Satoshi Kodera1, Hiroki Shinohara1, Kota Ninomiya1, Yasutomi Higashikuni1, Katsuhito Fujiu1, Hiroshi Akazawa1, Issei Komuro1 (1. Department of Cardiovascular Medicine, The University of Tokyo Hospital)

Keywords:small dataset, pretraining, 3D-CNN, echocardiogram

The development of deep learning algorithms usually requires large labeled training datasets. However, some kind of medical data, such as the echocardiogram videos of cardiac sarcoidosis, is highly difficult to collect. The purpose of this study was to develop a deep learning model to detect cardiac sarcoidosis using a small dataset of 302 echocardiogram videos. We compared several different model architectures including 2D and 3D models, and also discussed the effect of pretraining on a large open dataset of echocardiogram videos. We found that 3D models outperforms 2D models, and the pretraining improved the performance of the model from an AUC of 0.761 (95% CI 0.610, 0.911) to 0.841 (95% CI 0.716, 0.968).

Authentication for paper PDF access

A password is required to view paper PDFs. If you are a registered participant, please log on the site from Participant Log In.
You could view the PDF with entering the PDF viewing password bellow.