Research map: Artificial intelligence for the assessment of diastolic function

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Papers in this map

  1. Recommendations for the Evaluation of Left Ventricular Diastolic Function by Echocardiography: An Update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging · Sherif F. Nagueh · 2016 · 6819 citations · Cited by this paper
  2. Sodium reduction and salt substitutes: impact on blood pressure and recurrent stroke · 2026 · Related
  3. Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram · Zachi Itzhak Attia · 2018 · 1407 citations · Cited by this paper
  4. Artificial intelligence for right ventricular assessment: current evidence and future directions · 2026 · Related
  5. Phenomapping for Novel Classification of Heart Failure With Preserved Ejection Fraction · Sanjiv Jayendra Shah · 2014 · 1157 citations · Cited by this paper
  6. Postoperative atrial fibrillation after cardiac surgery: what is new? · 2025 · Related
  7. Video-based AI for beat-to-beat assessment of cardiac function · David Ouyang · 2020 · 1142 citations · Cited by this paper
  8. Artificial intelligence for left ventricular strain · 2026 · Related
  9. Fully Automated Echocardiogram Interpretation in Clinical Practice · Jeffrey Zhang · 2018 · 1018 citations · Cited by this paper
  10. Impact of social determinants of health on cardiovascular health · 2026 · Related
  11. Automatic diagnosis of the 12-lead ECG using a deep neural network · Antônio H. Ribeiro · 2020 · 882 citations · Cited by this paper
  12. Applications of genetic testing in cardiovascular disease · 2026 · Related
  13. Heart Failure with Preserved Ejection Fraction · Margaret M. Redfield · 2016 · 519 citations · Cited by this paper
  14. Current opinion in cardiology, epigenetics of heart failure · 2026 · Related
  15. Deep learning interpretation of echocardiograms · Amirata Ghorbani · 2020 · 501 citations · Cited by this paper
  16. Weight loss as the optimal cardiometabolic management strategy for preventing and treating heart failure · 2026 · Related
  17. Utility of a Deep-Learning Algorithm to Guide Novices to Acquire Echocardiograms for Limited Diagnostic Use · Akhil Narang · 2021 · 451 citations · Cited by this paper
  18. Optimizing conduits and intraoperative graft quality in coronary artery bypass graft surgery · 2026 · Related
  19. Recommendations for the Evaluation of Left Ventricular Diastolic Function by Echocardiography and for Heart Failure With Preserved Ejection Fraction Diagnosis: An Update From the American Society of Echocardiography · Sherif F. Nagueh · 2025 · 338 citations · Cited by this paper
  20. An Artificial Intelligence-Enabled Electrocardiogram to Evaluate Patients With Dyspnea in the Emergency Department · 2025 · Related
  21. Phenomapping of Patients with Heart Failure with Preserved Ejection Fraction Using Machine Learning-Based Unsupervised Cluster Analysis · Matthew W. Segar · 2019 · 319 citations · Cited by this paper
  22. Fully Automated Versus Standard Tracking of Left Ventricular Ejection Fraction and Longitudinal Strain · Christian Knackstedt · 2015 · 265 citations · Cited by this paper
  23. Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study · Jasper Tromp · 2021 · 197 citations · Cited by this paper
  24. Machine Learning Analysis of Left Ventricular Function to Characterize Heart Failure With Preserved Ejection Fraction · Sergio Sanchez‐Martinez · 2018 · 158 citations · Cited by this paper
  25. Identification of novel pheno-groups in heart failure with preserved ejection fraction using machine learning · Åsa K. Hedman · 2020 · 147 citations · Cited by this paper
  26. Building Digital Twins for Cardiovascular Health: From Principles to Clinical Impact · Kaan Sel · 2024 · 144 citations · Cited by this paper
  27. Deep-Learning Models for the Echocardiographic Assessment of Diastolic Dysfunction · Ambarish Pandey · 2021 · 132 citations · Cited by this paper
  28. Diagnosis of Heart Failure With Preserved Ejection Fraction: Machine Learning of Spatiotemporal Variations in Left Ventricular Deformation · Mahdi Tabassian · 2018 · 131 citations · Cited by this paper
  29. Automated Echocardiographic Detection of Heart Failure With Preserved Ejection Fraction Using Artificial Intelligence · Ashley Paul Akerman · 2023 · 115 citations · Cited by this paper
  30. Machine Learning Assessment of Left Ventricular Diastolic Function Based on Electrocardiographic Features · Nobuyuki Kagiyama · 2020 · 114 citations · Cited by this paper
  31. Precision Phenotyping in Heart Failure and Pattern Clustering of Ultrasound Data for the Assessment of Diastolic Dysfunction · Alaa Mabrouk Salem Omar · 2017 · 107 citations · Cited by this paper
  32. Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure · Eunjung Lee · 2024 · 103 citations · Cited by this paper
  33. Utilization of Artificial Intelligence in Echocardiography · Kenya Kusunose · 2019 · 102 citations · Cited by this paper
  34. Phenomapping in heart failure with preserved ejection fraction: insights, limitations, and future directions · Anthony E. Peters · 2022 · 89 citations · Cited by this paper
  35. AI-Assisted Echocardiographic Prescreening of Heart Failure With Preserved Ejection Fraction on the Basis of Intrabeat Dynamics · Yu-An Chiou · 2021 · 67 citations · Cited by this paper
  36. Automatic biplane left ventricular ejection fraction estimation with mobile point-of-care ultrasound using multi-task learning and adversarial training · Mohammad Hossein Jafari · 2019 · 57 citations · Cited by this paper
  37. Phenotyping heart failure using model‐based analysis and physiology‐informed machine learning · Edith Jones · 2021 · 53 citations · Cited by this paper
  38. Left Atrial Strain in the Assessment of Diastolic Function in Heart Failure: A Machine Learning Approach · Erberto Carluccio · 2023 · 53 citations · Cited by this paper
  39. Artificial Intelligence and Echocardiography · Yeonyee Elizabeth Yoon · 2021 · 49 citations · Cited by this paper

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