Attention Optimization in AI-Aided Drowning Diagnosis Using Post-Mortem CT to Mitigate Overfitting with Limited Training Data-Reference-Cited by-同舟云学术

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Attention Optimization in AI-Aided Drowning Diagnosis Using Post-Mortem CT to Mitigate Overfitting with Limited Training Data

Published:2024-06-30 Issue: Volume:32 Page:1-6
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
language:
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Author:

Zhang Zhang¹,Zhang Xiaoyong²,Mizuno Taihei³,Ichiji Kei¹,Homma Noriyasu⁴

Affiliation:

1. Tohoku University Graduate School of Medicine Center for Data-Driven Science and Artificial Intelligence, Tohoku University,Sendai,Japan

2. National Institute of Technology, Sendai College,Department of General Engineering,Sendai,Japan

3. Tohoku University,Graduate School of Biomedical Engineering,Sendai,Japan

4. Tohoku University Graduate School of Medicine Graduate School of Biomedical Engineering, Tohoku University,Sendai,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10650327.pdf?arnumber=10650327

Reference21 articles.

1. Machine Learning for Medical Imaging

2. Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning

3. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

4. Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier]

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