著者

Shunsuke Ogata Yoshito Ishi Keiichiro Asano Erena Kobayashi Shun Kubota Keita Takahashi Yosuke Miyaji Yuichi Higashiyama Hideto Joki Hiroshi Doi Michiaki Koga Hideyuki Takeuchi Fumiaki Tanaka

出版者

The Japanese Society of Internal Medicine

雑誌

Internal Medicine (ISSN:09182918)

巻号頁・発行日

pp.8967-21, (Released:2022-03-26)

参考文献数

9

被引用文献数

10

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Guillain-Barré syndrome (GBS) has occasionally occurred in people who have received coronavirus disease 2019 (COVID-19) vaccines. Dysgeusia is rare symptom of GBS. We herein report a rare case of sensory ataxic GBS with dysgeusia just after the second dose of the Pfizer-BioNTech COVID-19 vaccine. Although autoantibodies against glycolipids were not detected, immunotherapy with intravenous immunoglobulin and methylprednisolone pulse therapy effectively ameliorated the symptoms. Our report suggests that the COVID-19 vaccine may induce various clinical subtypes of GBS, including a rare variant with sensory ataxia and dysgeusia.

著者

Shunsuke Ogata Yoshito Ishii Keiichiro Asano Erena Kobayashi Shun Kubota Keita Takahashi Yosuke Miyaji Yuichi Higashiyama Hideto Joki Hiroshi Doi Michiaki Koga Hideyuki Takeuchi Fumiaki Tanaka

出版者

The Japanese Society of Internal Medicine

雑誌

Internal Medicine (ISSN:09182918)

巻号頁・発行日

vol.61, no.11, pp.1757-1760, 2022-06-01 (Released:2022-06-01)

参考文献数

9

被引用文献数

10

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Guillain-Barré syndrome (GBS) has occasionally occurred in people who have received coronavirus disease 2019 (COVID-19) vaccines. Dysgeusia is rare symptom of GBS. We herein report a rare case of sensory ataxic GBS with dysgeusia just after the second dose of the Pfizer-BioNTech COVID-19 vaccine. Although autoantibodies against glycolipids were not detected, immunotherapy with intravenous immunoglobulin and methylprednisolone pulse therapy effectively ameliorated the symptoms. Our report suggests that the COVID-19 vaccine may induce various clinical subtypes of GBS, including a rare variant with sensory ataxia and dysgeusia.

著者

Koichiro YAMANAKA Keita TAKAHASHI Toshiaki FUJII Ryuraroh MATSUMOTO

出版者

The Institute of Electronics, Information and Communication Engineers

雑誌

IEICE Transactions on Information and Systems (ISSN:09168532)

巻号頁・発行日

vol.E104.D, no.5, pp.785-788, 2021-05-01 (Released:2021-05-01)

参考文献数

15

被引用文献数

4

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Thanks to the excellent learning capability of deep convolutional neural networks (CNNs), CNN-based methods have achieved great success in computer vision and image recognition tasks. However, it has turned out that these methods often have inherent vulnerabilities, which makes us cautious of the potential risks of using them for real-world applications such as autonomous driving. To reveal such vulnerabilities, we propose a method of simultaneously attacking monocular depth estimation and optical flow estimation, both of which are common artificial-intelligence-based tasks that are intensively investigated for autonomous driving scenarios. Our method can generate an adversarial patch that can fool CNN-based monocular depth estimation and optical flow estimation methods simultaneously by simply placing the patch in the input images. To the best of our knowledge, this is the first work to achieve simultaneous patch attacks on two or more CNNs developed for different tasks.