Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Aortic Regurgitation II: Clinical Features and Diagnostic Tests01:22

Aortic Regurgitation II: Clinical Features and Diagnostic Tests

52
Aortic valve regurgitation (AR) occurs when the aortic valve fails to close properly, allowing blood to flow backward from the aorta into the left ventricle. This backflow can result in two distinct clinical presentations: acute and chronic AR, each characterized by its own set of symptoms and physical findings.Acute Aortic RegurgitationAcute AR presents with a sudden onset of severe symptoms. Patients typically experience profound dyspnea (shortness of breath), chest pain, and signs of left...
52
Aortic Regurgitation I: Introduction01:15

Aortic Regurgitation I: Introduction

36
IntroductionAortic regurgitation is characterized by the backward flow of blood from the aorta into the left ventricle during diastole and arises from the improper closure of the aortic valve. This condition results in left ventricular volume overload and can stem from both acute and chronic etiologies, each contributing uniquely to the disease's progression and symptomatology.Acute and Chronic CausesAcute aortic regurgitation often results from events that suddenly impair the integrity of the...
36
Aortic Regurgitation III: Medical Management01:25

Aortic Regurgitation III: Medical Management

42
Aortic regurgitation (AR) is when the aortic valve does not close or seal properly, leading to backward blood circulation from the aorta into the left ventricle during diastole. Common causes of AR include rheumatic heart disease, congenital valve defects, and aortic root dilation. Managing AR requires a multifaceted approach to alleviate symptoms, preserve left ventricular function, and address the underlying cause of the regurgitation. Patients with symptomatic AR or significant left...
42
Atherosclerosis II: Clinical Manifestations and Diagnostic Tests01:27

Atherosclerosis II: Clinical Manifestations and Diagnostic Tests

38
Atherosclerosis is a progressive disorder that leads to the thickening and narrowing of arterial walls due to plaque buildup. This condition can cause various symptoms depending on the arteries affected:Coronary Artery Disease (CAD): This condition affects the coronary arteries and may lead to chest pain (angina), shortness of breath (dyspnea), heart attacks, and other heart disease symptoms.Cerebrovascular Disease: This affects blood flow to the brain, causing transient ischemic attacks (TIAs)...
38

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Evaluating the UNICA system for the treatment of severe tricuspid regurgitation.

Future cardiology·2026
Same author

The Safety Profile of Ticagrelor Among Older Adults (age ≥ 75 years): A Pharmacovigilance Analysis.

Cardiology·2026
Same author

Safety and Feasibility of a CT-Based Pathway for Left Atrial Appendage Assessment Prior to Inpatient Cardioversion: A Single-Center Experience.

Clinical cardiology·2026
Same author

Dynamic Changes in Circulating Osteogenic Progenitor Cells Following TAVI: Implications for Vascular Remodeling-EPC and EPC-OCN Dynamics After TAVI.

Journal of clinical medicine·2026
Same author

Dysregulated metabolic homeostasis as a unifying death mechanism underlying the diverse clinical manifestations of COVID-19: insights from a retrospective analysis of sequential blood variables.

Frontiers in medicine·2026
Same author

Prognostic Impact of New-Onset Type 2 Diabetes Mellitus After Acute Myocardial Infarction: Long-Term Mortality Compared with Pre-Existing and No Diabetes.

Medicina (Kaunas, Lithuania)·2026

関連する実験動画

Updated: Sep 9, 2025

Author Spotlight: Development of a Minimally Invasive Large-Animal Model for Reliable and Reproducible Cardiovascular Research
06:51

Author Spotlight: Development of a Minimally Invasive Large-Animal Model for Reliable and Reproducible Cardiovascular Research

Published on: October 20, 2023

1.2K

人工知能による大動脈狭窄の進行予測:機械学習モデル

Edward Itelman1, Yaron Shapira1, Alon Shechter1

  • 1Department of Cardiology, Rabin Medical Center, Petah Tikva, Israel; Tel Aviv School of Medicine, Tel Aviv University, Tel Aviv, Israel.

JACC. Advances
|August 29, 2025
PubMed
まとめ

エコーカルディオグラフィーのレポートを用いた人工知能モデルは,大動脈狭窄症 (AS) から重症ASへの進行を予測できます. このツールは,パーソナライズされた患者管理のための早期のリスク識別に役立ちます.

キーワード:
大動脈狭窄症人工知能エコーカルディオグラフィー機械学習リスク予測バルブ病の進行

さらに関連する動画

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

4.0K
Measurement of Pulse Propagation Velocity, Distensibility and Strain in an Abdominal Aortic Aneurysm Mouse Model
09:32

Measurement of Pulse Propagation Velocity, Distensibility and Strain in an Abdominal Aortic Aneurysm Mouse Model

Published on: February 23, 2020

6.3K

関連する実験動画

Last Updated: Sep 9, 2025

Author Spotlight: Development of a Minimally Invasive Large-Animal Model for Reliable and Reproducible Cardiovascular Research
06:51

Author Spotlight: Development of a Minimally Invasive Large-Animal Model for Reliable and Reproducible Cardiovascular Research

Published on: October 20, 2023

1.2K
Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

4.0K
Measurement of Pulse Propagation Velocity, Distensibility and Strain in an Abdominal Aortic Aneurysm Mouse Model
09:32

Measurement of Pulse Propagation Velocity, Distensibility and Strain in an Abdominal Aortic Aneurysm Mouse Model

Published on: February 23, 2020

6.3K

科学分野:

  • 心臓病科
  • 医療用イメージング
  • 人工知能

背景:

  • 現在,大動脈狭窄 (AS) のモニタリングは,資源集約的なエコーカルディオグラフィに依存しています.
  • 連続エコーカルジオグラムの変動はASの進行の評価に課題をもたらします.
  • 人工知能 (AI) はASにおけるリスクの早期発見に役立つ可能性がある.

研究 の 目的:

  • ASの進行を予測するAIモデルを開発する.
  • このモデルはエコーカルディオグラフィーレポートのデータのみを使用しています.
  • モデルの予測的正確性と解釈性を評価する.

主な方法:

  • 軽度/中等度のAS患者の9,330回のエコーカルジオグラムを遡及的に分析した.
  • エコーカルディオグラフィーレポートデータのみを用いたAIモデルの開発.
  • 精度,AUC-ROC,および校正メトリックを用いた性能評価; SHAP値による解釈性.

主要な成果:

  • AIモデルはAUC-ROCを0.91と83%の精度で達成した.
  • 47%の患者は追跡期間中に重症なASへと進行した.
  • このモデルは強力な予測性能とカリブレーションを証明し,クロス・バリデーションによって検証された.

結論:

  • エコーカルディオグラフィーの報告に焦点を当てたAIモデルは,重度のAS進行のリスクのある患者を確実に特定します.
  • パーソナライズされたフォローアップと タイムリーな介入を 支援するツールです
  • 汎用性と臨床的有用性を確認するために,さらなる多センター検証が推奨されます.