2026-03-12T22:26:58Z https://ipsj.ixsq.nii.ac.jp/oai

oai:ipsj.ixsq.nii.ac.jp:00229903 2025-01-19T11:22:12Z 6504:11436:11440

複数学習モデルにvoting分類を用いた胸部X線画像から疾患のマルチラベル診断について ホンズオン, グェン 人工知能と認知科学 Early diagnosis of thorax diseases may improve a patient's chances of cure and recovery. Recently, deep learning approaches are applied to multilabel classification of chest X-ray images. However, multilabel causes imbalance in the train data is a problem that happens with a variety of data, especially health data. This study aims to improve the performance of diseases detection from X-ray images. After adjusting the balance of data sample among different disease labels, a voting classification method has been involved to combine the results from different models. As a result, a meaningful improvement has been achieved. conference paper 情報処理学会 2023-02-16 application/pdf 第85回全国大会講演論文集 1 2023 209 210 AN00349328 https://ipsj.ixsq.nii.ac.jp/record/229903/files/IPSJ-Z85-2Q-07.pdf jpn