Toba Shuhei 鳥羽修平

Researcher Number	20806111
Other IDs	https://orcid.org/0000-0002-2843-1086
Affiliation (Current)	2024: 三重大学, 医学部附属病院, 助教
Affiliation (based on the past Project Information) *help	2024: 三重大学, 医学部附属病院, 助教 2019 – 2022: 三重大学, 医学部附属病院, 助教
Review Section/Research Field	Principal Investigator Basic Section 53020:Cardiology-related Except Principal Investigator Basic Section 55030:Cardiovascular surgery-related / Basic Section 58010:Medical management and medical sociology-related / Basic Section 53020:Cardiology-related / Basic Section 55040:Respiratory surgery-related
Keywords	Principal Investigator 血行動態 / 胸部X線写真 / 人工知能 / deep learning / 機械学習 / 肺体血流比 / 胸部X線 / 学校心臓検診 / 小児 / 12誘導心電図 … More / 転移学習 / 基盤モデル / 胸部レントゲン写真 / 血行動態予測 / 先天性心疾患 … More Except Principal Investigator AI / Deep Learning / 神経損傷 / 静脈穿刺 / 人工知能 / 肺血行動態 / 肺循環疾患 / 胸部X線透視動画解析 / 3Dプリンター / 3Dアトラス / 心臓血管外科 / 刺激伝導系 / ３Dプリントモデル / 三次元アトラス / Micro-CT / 先天性心疾患 / 画像診断 / 早期肺癌 / Deep learning / CT画像 / MIA / AIS / CNN / 深層学習 / 機械学習 / CT / 早期肺腺癌 Less

肺循環障害の病態・重症度評価におけるX線透視動画解析法の応用
- Principal Investigator
  
  荻原義人
- Project Period (FY)
  2024 – 2026
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 53020:Cardiology-related
- Research Institution
  Mie University
AIを用いた血行動態指標の予測に関する研究
- Principal Investigator
  
  別所早紀
- Project Period (FY)
  2024 – 2026
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 55030:Cardiovascular surgery-related
- Research Institution
  Mie University
Deep Learningを活用した超音波ガイドによる安全な静脈穿刺法の開発
- Principal Investigator
  
  大橋啓之
- Project Period (FY)
  2024 – 2026
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 58010:Medical management and medical sociology-related
- Research Institution
  Mie University
Development and clinical application of a deep-learning model to predict hemodynamic parameters from chest radiographsPrincipal Investigator
- Principal Investigator
  
  鳥羽修平
- Project Period (FY)
  2021 – 2023
- Research Category
  
  Fund for the Promotion of Joint International Research (Fostering Joint International Research (A))
- Review Section
  
  Basic Section 53020:Cardiology-related
- Research Institution
  Mie University
Micro CTによる先天性心疾患の高精細3Dアトラス作成と心内組織三次元可視化
- Principal Investigator
  
  山崎誉斗
- Project Period (FY)
  2021 – 2024
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 55030:Cardiovascular surgery-related
- Research Institution
  Mie University
Diagnostic evaluation of early stage lung cancer using deep learning-based analysis of CT images
- Principal Investigator
  
  高尾仁二
- Project Period (FY)
  2020 – 2023
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 55040:Respiratory surgery-related
- Research Institution
  Mie University
Artificial intelligence-based analysis of chest X-ray to predict hemodynamic parametersPrincipal Investigator
- Principal Investigator
  
  Toba Shuhei
- Project Period (FY)
  2019 – 2022
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 53020:Cardiology-related
- Research Institution
  Mie University

All 2023 2022 2021 2020 2019

All Journal Article Presentation Book Patent

[Book] 「先天性心疾患と人工知能ー医師を代替するAI、超えるAIー」循環器内科, 91(4): 434-4392022
- Author(s)
  鳥羽修平、三谷義英
- Total Pages
  510
- Publisher
  科学評論社
- Data Source
  KAKENHI-PROJECT-20KK0375
[Book] 「先天性心疾患と人工知能ー医師を代替するAI、超えるAIー」循環器内科, 91(4): 434-4392022
- Author(s)
  鳥羽修平、三谷義英
- Total Pages
  510
- Publisher
  科学評論社
- Data Source
  KAKENHI-PROJECT-19K17559
[Journal Article] 先天性心疾患と人工知能－医師を代替するAI，超えるAI－2022
- Author(s)
  鳥羽修平, 三谷義英
- Journal Title
  
  循環器内科
  
  Volume: 91 Pages: 434-439
- Data Source
  KAKENHI-PROJECT-19K17559
[Journal Article] Prediction of Pulmonary to Systemic Flow Ratio in Patients With Congenital Heart Disease Using Deep Learning-Based Analysis of Chest Radiographs2020
- Author(s)
  Shuhei Toba, MD; Yoshihide Mitani, MD, PhD; Noriko Yodoya, MD; Hiroyuki Ohashi, MD; Hirofumi Sawada, MD, PhD; Hidetoshi Hayakawa,MD, PhD; Masahiro Hirayama, MD, PhD; Ayano Futsuki, MD; Naoki Yamamoto, MD; Hisato Ito,MD, PhD; Takeshi Konuma, MD, PhD; Hideto Shimpo,MD, PhD; Motoshi Takao, MD, PhD
- Journal Title
  
  JAMA Cardiology
  
  Volume: - Issue: 4 Pages: 449-457
- DOI
  10.1001/jamacardio.2019.5620
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-19K17559, KAKENHI-PROJECT-18K07841
[Patent] 評価システム、評価方法、学習方法、学習済みモデル、プログラム2019
- Inventor(s)
  鳥羽修平、三谷義英、高尾仁二
- Industrial Property Rights Holder
  三重大学
- Industrial Property Rights Type
  特許
- Industrial Property Number
  2019-178086
- Filing Date
  2019
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] Development of High-resolution 3-dimensional Atlas and Models of Congenital Heart Defects.2023
- Author(s)
  Shuhei Toba
- Organizer
  The 53rd Annual Meeting of the Japanese Society for Cardiovascular Surgery.
- Data Source
  KAKENHI-PROJECT-21K08860
[Presentation] Perioperative Changes of Pulmonary to Systemic Flow Ratio Predicted by Deep Learning-Based Analysis of Chest Radiographs in Patients with Atrial Septal Defect2023
- Author(s)
  Yusuke Sugitani, Shuhei Toba, Keishin Hattori, Umezu Kentaro, Yoshihide Mitani, Hirofumi Sawada, Hiroyuki Ohashi, Noriko Yodoya, Kazunobu Ohya, Naoki Tsuboya, Hisato Itoh, Yu Shomura, Masahiro Hirayama, Motoshi Takao
- Organizer
  第87回日本循環器学会学術集会
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] Quantitative analysis of hemodynamics from chest radiographs using deep learning.2022
- Author(s)
  Tsuji S, Toba S, Sato A, Sugitani R
- Organizer
  The 4th Annual Meeting of;Japanese;Association for;Medical Artificial Intelligence
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] 人工知能による胸部X線写真からの定量的血行動態予測2022
- Author(s)
  辻清龍, 鳥羽修平, 藤本直紀, 佐藤綾音, 土肥薫
- Organizer
  第70回日本心臓病学会学術集会
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] Development of base model for deep learning of chest radiographs.2022
- Author(s)
  Sato A, Toba S, Tsuji S, Sugitani R
- Organizer
  The 4th Annual Meeting of Japanese Association for Medical Artificial Intelligence. 2022年6月
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] Application of Deep Learning in Pediatric Cardiology2022
- Author(s)
  Shuhei Toba
- Organizer
  AHA & JSPCCS joint webinar (Artificial Intelligence and 3D Imaging in Pediatric Cardiology)
- Invited / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20KK0375
[Presentation] Deep Learning-based Analysis of 12-lead Electrocardiogram for Pediatric Cardiac Disease Mass Screening in School-age Children2021
- Author(s)
  Shuhei Toba, Yoshihide Mitani, et al.
- Organizer
  日本循環器学会学術総会　プレナリーセッション
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] 学校心臓検診心電図における人工知能の応用2021
- Author(s)
  鳥羽修平、三谷義英、杉谷侑亮、大橋啓之、澤田博文
- Organizer
  日本小児心電図学会学術総会　シンポジウム
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] Deep Learning-based Analysis of 12-lead Electrocardiogram for Pediatric Cardiac Disease Mass Screening in School-age Children2021
- Author(s)
  Shuhei Toba, Yoshihide Mitani, et al.
- Organizer
  日本循環器学会学術総会　プレナリーセッション
- Data Source
  KAKENHI-PROJECT-20KK0375
[Presentation] Deep learning-based analysis of 12-lead electrocardiogram for pediatric cardiac disease mass screening in school-age children2021
- Author(s)
  鳥羽修平、三谷義英、杉谷侑亮、ほか
- Organizer
  第85回日本循環器学会学術集会
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] Application of Deep Learning in Pediatric Cardiology2021
- Author(s)
  Shuhei Toba
- Organizer
  AHA & JSPCCS joint webinar (Artificial Intelligence and 3D Imaging in Pediatric Cardiology)
- Invited / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] 学校心臓検診心電図における人工知能の応用2021
- Author(s)
  鳥羽修平、三谷義英、et al.
- Organizer
  日本小児心電図学会学術総会　シンポジウム
- Data Source
  KAKENHI-PROJECT-20KK0375
[Presentation] 学校心臓検診心電図を自動判読する人工知能の開発2021
- Author(s)
  鳥羽修平，三谷義英、杉谷侑亮、大橋啓之，澤田博文，淀谷典子，大槻祥一郎、山崎誉斗，梅津健太郎
- Organizer
  日本小児循環器学会学術総会　パネルディスカッション
- Data Source
  KAKENHI-PROJECT-20KK0375
[Presentation] 学校心臓検診心電図を自動判読する人工知能の開発2021
- Author(s)
  鳥羽修平，三谷義英、杉谷侑亮、大橋啓之，澤田博文，淀谷典子，大槻祥一郎、山崎誉斗，梅津健太郎
- Organizer
  日本小児循環器学会学術総会　パネルディスカッション
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] Automated analysis of 12-lead electrocardiogram for pediatric cardiac disease mass screening in school-age children by the combined use of signal processing and deep learning2020
- Author(s)
  鳥羽修平、三谷義英、杉谷侑亮、ほか
- Organizer
  American Heart Association Scientific Sessions 2020
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] 先天性心疾患周術期における、胸部 X 線写真を用いた肺体血流比予測 AI (人工知能)の評価検討2019
- Author(s)
  鳥羽修平、小沼武司、石川廉太、山崎誉斗、金田真吏、伊藤温志、平野玲奈、夫津木綾乃、山本直樹、伊藤久人、島本亮、高尾仁二
- Organizer
  第62回関西胸部外科学会学術集会
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] 胸部レントゲン写真から肺体血流比を予測する回帰モデル（畳み込みニューラルネットワーク）における，精度向上の試み2019
- Author(s)
  杉谷侑亮、鳥羽修平、大橋啓之、三谷義英
- Organizer
  第2回日本メディカルAI学会
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] Deep learningを用いた，胸部X線写真から肺体血流比を予測する方法の開発2019
- Author(s)
  石川廉太、鳥羽修平、三谷義英、大矢和伸、淀谷典子、大橋啓之、澤田博文、山崎誉斗、夫津木綾乃、小沼武司
- Organizer
  第55回日本小児循環器学会総会・学術集会
- Data Source
  KAKENHI-PROJECT-19K17559
[Presentation] Quantitative Analysis Of Chest X-ray Using Deep Learning To Predict Pulmonary To Systemic Flow Ratio In Patients With Congenital Heart Disease2019
- Author(s)
  Shuhei Toba, Yoshihide Mitani, Noriko Yodoya, Hiroyuki Ohashi, Hirofumi Sawada, Hidetoshi Hayakawa, Masahiro Hirayama, Ayano Fusuki, Naoki Yamamoto, Hisato Ito, Takeshi Konuma, Hideto Shimpo, Motoshi Takao
- Organizer
  American Heart Association Scientific Sessions 2019
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K17559

1. 高尾仁二 (30263007)

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2. 伊藤久人 (40378336)

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3. 中山良平 (20402688)

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4. 金田真吏 (30793418)

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5. 内田克典 (60362349)

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6. 久保岡牧子 (60832524)

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7. 山崎誉斗 (00897754)

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8. 梅津健太郎 (30408596)

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9. 荻原義人 (70626572)

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10. 北川覚也 (50378353)

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11. 土肥薫 (50422837)

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12. 別所早紀 (30806112)

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13. 大橋啓之 (70397511)

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14. 澤田博文 (30362354)

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15. 三谷義英 (60273380)

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Toba Shuhei 鳥羽 修平

Research Projects

Research Products

Co-Researchers

肺循環障害の病態・重症度評価におけるX線透視動画解析法の応用

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

AIを用いた血行動態指標の予測に関する研究

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Deep Learningを活用した超音波ガイドによる安全な静脈穿刺法の開発

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development and clinical application of a deep-learning model to predict hemodynamic parameters from chest radiographsPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Micro CTによる先天性心疾患の高精細3Dアトラス作成と心内組織三次元可視化

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Diagnostic evaluation of early stage lung cancer using deep learning-based analysis of CT images

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Artificial intelligence-based analysis of chest X-ray to predict hemodynamic parametersPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Book] 「先天性心疾患と人工知能ー医師を代替するAI、超えるAIー」循環器内科, 91(4): 434-4392022

Author(s)

Total Pages

Publisher

Data Source

[Book] 「先天性心疾患と人工知能ー医師を代替するAI、超えるAIー」循環器内科, 91(4): 434-4392022

Author(s)

Total Pages

Publisher

Data Source

[Journal Article] 先天性心疾患と人工知能－医師を代替するAI，超えるAI－2022

Author(s)

Journal Title

Data Source

[Journal Article] Prediction of Pulmonary to Systemic Flow Ratio in Patients With Congenital Heart Disease Using Deep Learning-Based Analysis of Chest Radiographs2020

Author(s)

Journal Title

DOI

Data Source

[Patent] 評価システム、評価方法、学習方法、学習済みモデル、プログラム2019

Inventor(s)

Industrial Property Rights Holder

Industrial Property Rights Type

Industrial Property Number

Filing Date

Data Source

[Presentation] Development of High-resolution 3-dimensional Atlas and Models of Congenital Heart Defects.2023

Author(s)

Organizer

Data Source

[Presentation] Perioperative Changes of Pulmonary to Systemic Flow Ratio Predicted by Deep Learning-Based Analysis of Chest Radiographs in Patients with Atrial Septal Defect2023

Author(s)

Organizer

Data Source

Toba Shuhei 鳥羽修平