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SHINOHARA HIROKI  篠原 宏樹

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篠原 宏樹  シノハラ ヒロキ

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Researcher Number 70790351
Other IDs
Affiliation (Current) 2026: 東京大学, 医学部附属病院, 助教
Affiliation (based on the past Project Information) *help 2024: 東京大学, 医学部附属病院, 助教
2023: 東京大学, 医学部附属病院, 特任臨床医
Review Section/Research Field
Principal Investigator
Basic Section 53020:Cardiology-related
Keywords
Principal Investigator
人工知能 / マルチモーダルデータ / 人工知能(AI) / 循環器疾患 / 予後予測 / マルチモダリティ / 深層学習 / 虚血性心疾患 / 機械学習
  • Research Projects

    (1 results)
  • Research Products

    (2 results)
  •  Research on Prediction of Cardiac Disease Outcomes Using Multi-Modal Data Integration Approach Artificial IntelligencePrincipal Investigator

    • Principal Investigator
      篠原 宏樹
    • Project Period (FY)
      2023 – 2025
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 53020:Cardiology-related
    • Research Institution
      The University of Tokyo

All 2025 2024

All Journal Article Presentation

  • [Journal Article] The potential of the transformer-based survival analysis model, SurvTrace, for predicting recurrent cardiovascular events and stratifying high-risk patients with ischemic heart disease2024

    • Author(s)
      Shinohara Hiroki、Kodera Satoshi、Nagae Yugo、Hiruma Takashi、Kobayashi Atsushi、Sato Masataka、Sawano Shinnosuke、Kamon Tatsuya、Narita Koichi、Hirose Kazutoshi、Kiriyama Hiroyuki、Saito Akihito、Miura Mizuki、Minatsuki Shun、Kikuchi Hironobu、Takeda Norifumi、Akazawa Hiroshi、Morita Hiroyuki、Komuro Issei
    • Journal Title

      PLOS ONE

      Volume: 19 Issue: 6 Pages: e0304423-e0304423

    • DOI

      10.1371/journal.pone.0304423

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-23K15152
  • [Presentation] AssessingtheEfficacyoftheNewModelBasedonRTMDetinCoronaryStenosisDetection ComparedtoFaster R-CNN2025

    • Author(s)
      篠原宏樹
    • Organizer
      第89回日本循環器学会学術集会
    • Data Source
      KAKENHI-PROJECT-23K15152

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