High spatial endothelial shear stress gradient independently predicts site of acute coronary plaque rupture and erosion von Thondapu, Vikas, Mamon, Chris, Poon, Eric K W, Kurihara, Osamu, Kim, Hyung Oh, Russo, Michele, Araki, Makoto, Shinohara, Hiroki, Yamamoto, Erika, Dijkstra, Jouke, Tacey, Mark, Lee, Hang, Ooi, Andrew, Barlis, Peter, Jang, Ik-Kyung

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Diagnosing Heart Failure from Chest X-Ray Images Using Deep Learning von Matsumoto, Takuya, Kodera, Satoshi, Shinohara, Hiroki, Ieki, Hirotaka, Yamaguchi, Toshihiro, Higashikuni, Yasutomi, Kiyosue, Arihiro, Ito, Kaoru, Ando, Jiro, Takimoto, Eiki, Akazawa, Hiroshi, Morita, Hiroyuki, Komuro, Issei

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Deep Learning Algorithm to Detect Cardiac Sarcoidosis From Echocardiographic Movies von Katsushika, Susumu, Kodera, Satoshi, Nakamoto, Mitsuhiko, Ninomiya, Kota, Kakuda, Nobutaka, Shinohara, Hiroki, Matsuoka, Ryo, Ieki, Hirotaka, Uehara, Masae, Higashikuni, Yasutomi, Nakanishi, Koki, Nakao, Tomoko, Takeda, Norifumi, Fujiu, Katsuhito, Daimon, Masao, Ando, Jiro, Akazawa, Hiroshi, Morita, Hiroyuki, Komuro, Issei

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Predictors for layered coronary plaques: an optical coherence tomography study von Araki, Makoto, Yonetsu, Taishi, Russo, Michele, Kurihara, Osamu, Kim, Hyung Oh, Shinohara, Hiroki, Thondapu, Vikas, Soeda, Tsunenari, Minami, Yoshiyasu, Higuma, Takumi, Lee, Hang, Kakuta, Tsunekazu, Jang, Ik-Kyung

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Automatic Detection of Left Ventricular Dilatation and Hypertrophy from Electrocardiograms Using Deep Learning von Kokubo, Takahiro, Kodera, Satoshi, Sawano, Shinnosuke, Katsushika, Susumu, Nakamoto, Mitsuhiko, Takeuchi, Hirotoshi, Kimura, Nisei, Shinohara, Hiroki, Matsuoka, Ryo, Nakanishi, Koki, Nakao, Tomoko, Higashikuni, Yasutomi, Takeda, Norifumi, Fujiu, Katsuhito, Daimon, Masao, Akazawa, Hiroshi, Morita, Hiroyuki, Matsuyama, Yutaka, Komuro, Issei

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Automatic detection of vessel structure by deep learning using intravascular ultrasound images of the coronary arteries von Shinohara, Hiroki, Kodera, Satoshi, Ninomiya, Kota, Nakamoto, Mitsuhiko, Katsushika, Susumu, Saito, Akihito, Minatsuki, Shun, Kikuchi, Hironobu, Kiyosue, Arihiro, Higashikuni, Yasutomi, Takeda, Norifumi, Fujiu, Katsuhito, Ando, Jiro, Akazawa, Hiroshi, Morita, Hiroyuki, Komuro, Issei

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Applying masked autoencoder-based self-supervised learning for high-capability vision transformers of electrocardiographies von Sawano, Shinnosuke, Kodera, Satoshi, Setoguchi, Naoto, Tanabe, Kengo, Kushida, Shunichi, Kanda, Junji, Saji, Mike, Nanasato, Mamoru, Maki, Hisataka, Fujita, Hideo, Kato, Nahoko, Watanabe, Hiroyuki, Suzuki, Minami, Takahashi, Masao, Sawada, Naoko, Yamasaki, Masao, Sato, Masataka, Katsushika, Susumu, Shinohara, Hiroki, Takeda, Norifumi, Fujiu, Katsuhito, Daimon, Masao, Akazawa, Hiroshi, Morita, Hiroyuki, Komuro, Issei

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The Effectiveness of a Deep Learning Model to Detect Left Ventricular Systolic Dysfunction from Electrocardiograms von Katsushika, Susumu, Kodera, Satoshi, Nakamoto, Mitsuhiko, Ninomiya, Kota, Inoue, Shunsuke, Sawano, Shinnosuke, Kakuda, Nobutaka, Takiguchi, Hiroshi, Shinohara, Hiroki, Matsuoka, Ryo, Ieki, Hirotaka, Higashikuni, Yasutomi, Nakanishi, Koki, Nakao, Tomoko, Seki, Tomohisa, Takeda, Norifumi, Fujiu, Katsuhito, Daimon, Masao, Akazawa, Hiroshi, Morita, Hiroyuki, Komuro, Issei

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Clinical significance of healed plaque detected by optical coherence tomography: a 2-year follow-up study von Kurihara, Osamu, Russo, Michele, Kim, Hyung Oh, Araki, Makoto, Shinohara, Hiroki, Lee, Hang, Takano, Masamichi, Mizuno, Kyoichi, Jang, Ik-Kyung

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Factors associated with left ventricular reverse remodelling after percutaneous coronary intervention in patients with left ventricular systolic dysfunction von Adachi, Yusuke, Kiyosue, Arihiro, Ando, Jiro, Kawahara, Takuya, Kodera, Satoshi, Minatsuki, Shun, Kikuchi, Hironobu, Inaba, Toshiro, Kiriyama, Hiroyuki, Hirose, Kazutoshi, Shinohara, Hiroki, Saito, Akihito, Fujiwara, Takayuki, Hara, Hironori, Ueda, Kazutaka, Sakakura, Kenichi, Hatano, Masaru, Harada, Mutsuo, Takimoto, Eiki, Akazawa, Hiroshi, Morita, Hiroyuki, Momomura, Shin-ichi, Fujita, Hideo, Komuro, Issei

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Comparison of post‐stent optical coherence tomography findings: Layered versus non‐layered culprit lesions von Kurihara, Osamu, Shinohara, Hiroki, Kim, Hyung Oh, Russo, Michele, Araki, Makoto, Nakajima, Akihiro, Lee, Hang, Takano, Masamichi, Mizuno, Kyoichi, Komuro, Issei, Jang, Ik‐Kyung

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Deep learning model to detect significant aortic regurgitation using electrocardiography von Sawano, Shinnosuke, Kodera, Satoshi, Katsushika, Susumu, Nakamoto, Mitsuhiko, Ninomiya, Kota, Shinohara, Hiroki, Higashikuni, Yasutomi, Nakanishi, Koki, Nakao, Tomoko, Seki, Tomohisa, Takeda, Norifumi, Fujiu, Katsuhito, Daimon, Masao, Akazawa, Hiroshi, Morita, Hiroyuki, Komuro, Issei

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Age prediction from coronary angiography using a deep neural network: Age as a potential label to extract prognosis-related imaging features von Sawano, Shinnosuke, Kodera, Satoshi, Sato, Masataka, Katsushika, Susumu, Sukeda, Issei, Takeuchi, Hirotoshi, Shinohara, Hiroki, Kobayashi, Atsushi, Takiguchi, Hiroshi, Hirose, Kazutoshi, Kamon, Tatsuya, Saito, Akihito, Kiriyama, Hiroyuki, Miura, Mizuki, Minatsuki, Shun, Kikuchi, Hironobu, Higashikuni, Yasutomi, Takeda, Norifumi, Fujiu, Katsuhito, Ando, Jiro, Akazawa, Hiroshi, Morita, Hiroyuki, Komuro, Issei

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Deep Learning Models for Predicting Left Heart Abnormalities From Single-Lead Electrocardiogram for the Development of Wearable Devices von Sato, Masataka, Kodera, Satoshi, Setoguchi, Naoto, Tanabe, Kengo, Kushida, Shunichi, Kanda, Junji, Saji, Mike, Nanasato, Mamoru, Maki, Hisataka, Fujita, Hideo, Kato, Nahoko, Watanabe, Hiroyuki, Suzuki, Minami, Takahashi, Masao, Sawada, Naoko, Yamasaki, Masao, Sawano, Shinnosuke, Katsushika, Susumu, Shinohara, Hiroki, Takeda, Norifumi, Fujiu, Katsuhito, Daimon, Masao, Akazawa, Hiroshi, Morita, Hiroyuki, Komuro, Issei

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Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis von Ieki, Hirotaka, Ito, Kaoru, Saji, Mike, Kawakami, Rei, Nagatomo, Yuji, Takada, Kaori, Kariyasu, Toshiya, Machida, Haruhiko, Koyama, Satoshi, Yoshida, Hiroki, Kurosawa, Ryo, Matsunaga, Hiroshi, Miyazawa, Kazuo, Ozaki, Kouichi, Onouchi, Yoshihiro, Katsushika, Susumu, Matsuoka, Ryo, Shinohara, Hiroki, Yamaguchi, Toshihiro, Kodera, Satoshi, Higashikuni, Yasutomi, Fujiu, Katsuhito, Akazawa, Hiroshi, Iguchi, Nobuo, Isobe, Mitsuaki, Yoshikawa, Tsutomu, Komuro, Issei

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Efficacy of Fractional Flow Reserve-Guided Percutaneous Cornary Intervention for Patients with Angina Pectoris: A Network Meta-Analysis von Shinohara, Hiroki, Kodera, Satoshi, Kiyosue, Arihiro, Ando, Jiro, Morita, Hiroyuki, Komuro, Issei

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Multimodality Risk Assessment of Patients with Ischemic Heart Disease Using Deep Learning Models Applied to Electrocardiograms and Chest X-rays von Sawano, Shinnosuke, Kodera, Satoshi, Sato, Masataka, Shinohara, Hiroki, Kobayashi, Atsushi, Takiguchi, Hiroshi, Hirose, Kazutoshi, Kamon, Tatsuya, Saito, Akihito, Kiriyama, Hiroyuki, Miura, Mizuki, Minatsuki, Shun, Kikuchi, Hironobu, Takeda, Norifumi, Morita, Hiroyuki, Komuro, Issei

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Achalasia with esophageal intramural hematoma treated by per‐oral endoscopic myotomy (POEM) von Fujiyoshi, Yusuke, Fujiyoshi, Mary Raina Angeli, Kimura, Ryusuke, Shinohara, Hiroki, Nishikawa, Yohei, Shimamura, Yuto, Ikeda, Haruo, Onimaru, Manabu, Inoue, Haruhiro

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An explainable artificial intelligence-enabled electrocardiogram analysis model for the classification of reduced left ventricular function von Katsushika, Susumu, Kodera, Satoshi, Sawano, Shinnosuke, Shinohara, Hiroki, Setoguchi, Naoto, Tanabe, Kengo, Higashikuni, Yasutomi, Takeda, Norifumi, Fujiu, Katsuhito, Daimon, Masao, Akazawa, Hiroshi, Morita, Hiroyuki, Komuro, Issei

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Noncompaction of the Ventricular Myocardium and Polycystic Kidney Disease: A Case Report von Fukino, Keiko, MD, PhD, Ishiwata, Junpei, MD, Shinohara, Hiroki, MD, Oshima, Tsukasa, MD, Kozaki, Tsunashi, MD, PhD, Ikutomi, Masayasu, MD, PhD, Amaki, Toshihiro, MD, PhD, Nakamura, Fumitaka, MD, PhD

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