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日本語(JA) https:// companydata.tsujigawa.com/pres s-20261023-002/ AI医療機器の研究開発および遠隔医療サービスの社会実装に取り組むAMI株式会社（本社：鹿児島県鹿児島市、代表取締役CEO：小川晋平）は、熊本大学との共同研究において、わずか8秒間の心音と心電の情報から「大動脈

AI model estimates aortic stenosis from 8-second heart sound and ECG data

By PulseAugur Editorial · [1 sources] ·

AMI Inc. has announced a breakthrough in AI-powered medical diagnostics through a joint research initiative with Kumamoto University. The AI model, developed by AMI Inc. and validated by researchers at Kumamoto University, can estimate the presence of aortic stenosis using just 8 seconds of heart sound and electrocardiogram data. This research, a collaboration involving Professor Kenichi Tsujita and Lecturer Masamasa Ishii, has had its findings published in the international academic journal "Clinical Cardiology." AI

IMPACT This AI model could significantly improve early detection of aortic stenosis, potentially leading to faster treatment and better patient outcomes.

RANK_REASON Research publication in an international academic journal detailing a new AI model's diagnostic capabilities. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI model estimates aortic stenosis from 8-second heart sound and ECG data

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Research publication in an international academic journal detailing a new AI model's diagnostic capabilities. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 日本語(JA) · givers ·

    AMI Inc. (Headquarters: Kagoshima City, Kagoshima Prefecture, CEO: Shinpei Ogawa), which is engaged in the research and development of AI medical devices and the social implementation of remote medical services, has, in joint research with Kumamoto University, developed a method to detect "aortic" from just 8 seconds of heart sound and electrocardiogram information.

    https:// companydata.tsujigawa.com/pres s-20261023-002/ AI医療機器の研究開発および遠隔医療サービスの社会実装に取り組むAMI株式会社（本社：鹿児島県鹿児島市、代表取締役CEO：小川晋平）は、熊本大学との共同研究において、わずか8秒間の心音と心電の情報から「大動脈弁狭窄症」を推定するAIモデルの診断性能を検証し、その研究成果が国際学術誌「Clinical Cardiology」に掲載されたことを発表しました。本研究は、熊本大学大学院生命科学研究部 循環器内科学の辻田賢一教授、熊本大学病院 医療情報経…

    LINKS companydata.tsujigawa.com/press-20261023-… companydata.tsujigawa.com/…/1130001056317 companydata.tsujigawa.com/…/press-release… companydata.tsujigawa.com/company-map

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