Ieki Hirotaka 家城博隆

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家城博隆イエキヒロタカ

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Researcher Number	30932834
Other IDs
Affiliation (Current)	2026: 国立研究開発法人理化学研究所, 生命医科学研究センター, 学振特別研究員CPD
Affiliation (based on the past Project Information) *help	2024: 国立研究開発法人理化学研究所, 生命医科学研究センター, 学振特別研究員CPD 2022 – 2023: 国立研究開発法人理化学研究所, 生命医科学研究センター, 訪問研究員 2022: 国立研究開発法人理化学研究所, 生命医科学研究センター, 特別研究員(CPD)
Review Section/Research Field	Principal Investigator Basic Section 53020:Cardiology-related Except Principal Investigator Basic Section 53020:Cardiology-related
Keywords	Principal Investigator 人工知能 / 遺伝的リスクスコア / ゲノム医療 / 虚血性心疾患 / ゲノム Except Principal Investigator 胸部X線 / 全ゲノムシークエンス / 機械学習 / 心筋梗塞 / 心疾患 / オミックス

Artificial intelligence-based genome analysis of coronary artery disease to realize precision healthPrincipal Investigator
- Principal Investigator
  
  家城博隆
- Project Period (FY)
  2022 – 2025
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 53020:Cardiology-related
- Research Institution
  Institute of Physical and Chemical Research
Multi-omics data analysis using machine learning for precision medicine in coronary artery diseaseResearch Fellow
- Principal Investigator
  
  家城博隆
- Research Fellow
  
  家城博隆
- Project Period (FY)
  2022 – 2026
- Research Category
  
  Grant-in-Aid for JSPS Fellows
- Review Section
  
  Basic Section 53020:Cardiology-related
- Research Institution
  Institute of Physical and Chemical Research

All 2025 2024 2023 2022

All Journal Article Presentation

[Journal Article] Artificial intelligence automation of echocardiographic measurements2025
- Author(s)
  Sahashi Yuki、Ieki Hirotaka、Yuan Victoria、Christensen Matthew、Vukadinovic Milos、Binder-Rodriguez Christina、Rhee Justin、Zou James Y.、He Bryan、Cheng Paul、Ouyang David
- Journal Title
  
  medRxiv
  
  Volume: -
- DOI
  10.1101/2025.03.18.25324215
- Open Access
- Data Source
  KAKENHI-PROJECT-22K16128, KAKENHI-PROJECT-22KJ3142
[Journal Article] Automated Aortic Regurgitation Detection and Quantification: A Deep Learning Approach Using Multi-View Echocardiography2025
- Author(s)
  Binder Christina、Sahashi Yuki、Ieki Hirotaka、Vukadinovic Milos、Yuan Victoria、Rawlani Meenal、Cheng Paul、Ouyang David、Siegel Robert J.
- Journal Title
  
  medRxiv
  
  Volume: -
- DOI
  10.1101/2025.03.18.25323918
- Open Access
- Data Source
  KAKENHI-PROJECT-22KJ3142
[Journal Article] Artificial Intelligence Prediction of Age from Echocardiography as a Marker for Cardiovascular Disease2025
- Author(s)
  Rawlani Meenal、Ieki Hirotaka、Binder Christina、Yuan Victoria、Chiu I-Min、Bhatt Ankeet、Ebinger Joseph E.、Sahashi Yuki、Ambrosy Andrew P.、Cheng Paul、Kwan Alan C.、Cheng Susan、Ouyang David
- Journal Title
  
  medRxiv
  
  Volume: -
- DOI
  10.1101/2025.03.25.25324627
- Open Access
- Data Source
  KAKENHI-PROJECT-22K16128, KAKENHI-PROJECT-22KJ3142
[Journal Article] Detection of Left Ventricular Outflow Obstruction from Standard B-Mode Echocardiogram Videos using Deep Learning2025
- Author(s)
  Yuan Victoria、Ieki Hirotaka、Binder Christina、Sahashi Yuki、Cheng Paul C.、Ouyang David
- Journal Title
  
  medRxiv
  
  Volume: -
- DOI
  10.1101/2025.03.02.25323199
- Open Access
- Data Source
  KAKENHI-PROJECT-22K16128, KAKENHI-PROJECT-22KJ3142
[Journal Article] Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in the Japanese Population2024
- Author(s)
  Ieki Hirotaka、Ito Kaoru、Zhang Sai、et al.
- Journal Title
  
  medRxiv
  
  Volume: -
- DOI
  10.1101/2024.08.13.24311909
- Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K16128, KAKENHI-PROJECT-22KJ3142
[Journal Article] 【Expertise】ウェアラブルデバイスによる健康管理の未来　　家城博隆2024
- Author(s)
  家城博隆
- Journal Title
  
  Heart View AIとともに歩む，これからの循環器診療
  
  Volume: 12月号
- Data Source
  KAKENHI-PROJECT-22KJ3142
[Journal Article] Genome-wide analysis of heart failure yields insights into disease heterogeneity and enables prognostic prediction in the Japanese population2024
- Author(s)
  Enzan Nobuyuki、Miyazawa Kazuo、Koyama Satoshi、Kurosawa Ryo、Ieki Hirotaka、et al.
- Journal Title
  
  medRxiv
  
  Volume: -
- DOI
  10.1101/2024.11.14.24317249
- Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K16128, KAKENHI-PROJECT-22KJ3142
[Journal Article] 超の世界 “X線年齢という新しい健康指標 - レントゲン写真一枚から手軽に算出”2023
- Author(s)
  伊藤薫、家城博隆
- Journal Title
  
  自動車技術
  
  Volume: 77 Pages: 132-134
- Data Source
  KAKENHI-PROJECT-22KJ3142
[Journal Article] Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction2023
- Author(s)
  Miyazawa Kazuo、Ito Kaoru、Ito Masamichi、Zou Zhaonan、Kubota Masayuki、Nomura Seitaro、Matsunaga Hiroshi、Koyama Satoshi、Ieki Hirotaka、et al.
- Journal Title
  
  Nature Genetics
  
  Volume: 55 Issue: 2 Pages: 187-197
- DOI
  10.1038/s41588-022-01284-9
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K16128, KAKENHI-PROJECT-21H05045, KAKENHI-PROJECT-21H02919, KAKENHI-PROJECT-20J01343, KAKENHI-PROJECT-22KJ1890, KAKENHI-PROJECT-19H03649, KAKENHI-PROJECT-21K08023, KAKENHI-PROJECT-22H00471, KAKENHI-PROJECT-22KJ3142, KAKENHI-PROJECT-20H03525, KAKENHI-PROJECT-23K24602
[Journal Article] 超の世界　“X線年齢という新しい健康指標 - レントゲン写真一枚から手軽に算出”2023
- Author(s)
  伊藤　薫、家城　博隆
- Journal Title
  
  自動車技術
  
  Volume: 77 Pages: 132-134
- Data Source
  KAKENHI-PROJECT-22K16128
[Journal Article] Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis2022
- Author(s)
  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
- Journal Title
  
  Communications Medicine
  
  Volume: 2 Issue: 1 Pages: 159-159
- DOI
  10.1038/s43856-022-00220-6
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K07643, KAKENHI-PROJECT-22K16128, KAKENHI-PROJECT-21H02919, KAKENHI-PROJECT-21K08023, KAKENHI-PROJECT-22KJ3142
[Presentation] Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease2025
- Author(s)
  Hirotaka Ieki, Kaoru Ito, Sai Zhang, Satoshi Koyama, Martin Kjellberg, Michael Snyder, Issei Komuro
- Organizer
  The 89th Annual Scientific Meeting of the Japanese Circulation Society, Mar 29 2025, Yokohama, Japan
- Data Source
  KAKENHI-PROJECT-22KJ3142
[Presentation] Whole genome sequencing analysis reveals rare variant contribution to coronary artery disease in the Japanese population2024
- Author(s)
  Hirotaka Ieki, Kaoru Ito, Sai Zhang, Satoshi Koyama, Martin Kjellberg, Michael Snyder, Issei Komuro
- Organizer
  American Society of Human Genetics Annual Meeting 2024, Nov 7 2025, Denver, USA
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22KJ3142
[Presentation] Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in Japanese Population2024
- Author(s)
  Hirotaka Ieki, Kaoru Ito, Sai Zhang, Satoshi Koyama, Martin Kjellberg, Michael Snyder, Issei Komuro
- Organizer
  The American Heart Association (AHA) Scientific Sessions 2024. Chicago, USA. November 15-18th, 2024
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K16128
[Presentation] Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease2024
- Author(s)
  Hirotaka Ieki, Kaoru Ito, Sai Zhang, Satoshi Koyama, Martin Kjellberg, Michael Snyder, Issei Komuro
- Organizer
  The Cardiovascular Research Symposium. Stanford, USA. Aug 14th - 15th 2024
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K16128

1. 町田治彦

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results

Ieki Hirotaka 家城 博隆

家城 博隆 イエキ ヒロタカ

Research Projects

Research Products

Co-Researchers

Artificial intelligence-based genome analysis of coronary artery disease to realize precision healthPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Multi-omics data analysis using machine learning for precision medicine in coronary artery diseaseResearch Fellow

Principal Investigator

Research Fellow

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Artificial intelligence automation of echocardiographic measurements2025

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Automated Aortic Regurgitation Detection and Quantification: A Deep Learning Approach Using Multi-View Echocardiography2025

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Artificial Intelligence Prediction of Age from Echocardiography as a Marker for Cardiovascular Disease2025

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Detection of Left Ventricular Outflow Obstruction from Standard B-Mode Echocardiogram Videos using Deep Learning2025

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in the Japanese Population2024

Author(s)

Journal Title

DOI

Data Source

[Journal Article] 【Expertise】ウェアラブルデバイスによる健康管理の未来 家城博隆2024

Author(s)

Journal Title

Data Source

[Journal Article] Genome-wide analysis of heart failure yields insights into disease heterogeneity and enables prognostic prediction in the Japanese population2024

Author(s)

Journal Title

DOI

Data Source

[Journal Article] 超の世界 “X線年齢という新しい健康指標 - レントゲン写真一枚から手軽に算出”2023

Author(s)

Journal Title

Data Source

[Journal Article] Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] 超の世界 “X線年齢という新しい健康指標 - レントゲン写真一枚から手軽に算出”2023

Author(s)

Journal Title

Data Source

[Journal Article] Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis2022

Author(s)

Journal Title

DOI

Data Source

[Presentation] Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease2025

Author(s)

Organizer

Data Source

[Presentation] Whole genome sequencing analysis reveals rare variant contribution to coronary artery disease in the Japanese population2024

Author(s)

Organizer

Data Source

[Presentation] Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in Japanese Population2024

Author(s)

Ieki Hirotaka 家城博隆

家城博隆イエキヒロタカ

[Journal Article] 【Expertise】ウェアラブルデバイスによる健康管理の未来　　家城博隆2024

[Journal Article] 超の世界　“X線年齢という新しい健康指標 - レントゲン写真一枚から手軽に算出”2023