Most cited papers in Phonocardiography and Auscultation Techniques
What are the most cited papers in Phonocardiography and Auscultation Techniques?
The most cited paper in Phonocardiography and Auscultation Techniques is "Table of Integrals, Series, and Products" (I. S. Gradshteyn, I. M. Ryzhik, Alan Jeffrey et al., 1981), with 3,295 citations. Next come "Relevance of Lung Ultrasound in the Diagnosis of Acute Respiratory Failure*: The BLUE Protocol" (2,091) and "General considerations for lung function testing" (2,056).
Showing 50 of 99 papers. Every paper with more than 312 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Table of Integrals, Series, and Products I. S. Gradshteyn, I. M. Ryzhik, Alan Jeffrey et al. · Journal of Biomechanical Engineering | Feb 1981 | 3,295 |
| 2 | Relevance of Lung Ultrasound in the Diagnosis of Acute Respiratory Failure*: The BLUE Protocol Daniel A. Lichtenstein, Gilbert A. Mezière · CHEST Journal | 10 Apr 2008 | 2,091 |
| 3 | General considerations for lung function testing Martin R. Miller, Robert O. Crapo, J. Hankinson et al. · European Respiratory Journal | 30 Jun 2005 | 2,056 |
| 4 | Automatic Classification of Heartbeats Using ECG Morphology and Heartbeat Interval Features Philip de Chazal, Muireann O’Dwyer, Richard B. Reilly · IEEE Transactions on Biomedical Engineering | 21 Jun 2004 | 1,684 |
| 5 | Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification Justin Salamon, Juan Pablo Bello · IEEE Signal Processing Letters | 23 Jan 2017 | 1,357 |
| 6 | On empirical mode decomposition and its algorithms Gabriel Rilling, Patrick Flandrin, Paulo Gonçalvès | Jun 2003 | 1,329 |
| 7 | Systolic Time Intervals in Heart Failure in Man Arnold M. Weissler, Willard S. Harris, Clyde D. Schoenfeld · Circulation | Feb 1968 | 1,227 |
| 8 | Comparative Diagnostic Performances of Auscultation, Chest Radiography, and Lung Ultrasonography in Acute Respiratory Distress Syndrome Daniel A. Lichtenstein, Ivan Goldstein, Eric Mourgeon et al. · Anesthesiology | 24 Dec 2003 | 1,089 |
| 9 | Scalp electrode impedance, infection risk, and EEG data quality Thomas C. Ferrée, Phan Luu, Gerald S. Russell et al. · Clinical Neurophysiology | Mar 2001 | 1,020 |
| 10 | Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals U. Rajendra Acharya, Hamido Fujita, Shu Lih Oh et al. · Information Sciences | 23 Jun 2017 | 951 |
| 11 | Defining the Sudden Infant Death Syndrome (Sids): Deliberations of an Expert Panel Convened by the National Institute of Child Health and Human Development Marian Willinger, L. Stanley James, CHARLOTTE S. CATZ · Pediatric Pathology | 1991 | 937 |
| 12 | FIGO consensus guidelines on intrapartum fetal monitoring: Cardiotocography Diogo Ayres‐de‐Campos, Catherine Y. Spong, Edwin Chandraharan et al. · International Journal of Gynecology & Obstetrics | 30 Sep 2015 | 920 |
| 13 | Cape Town, South Africa David M. Ridley, Harold V. F. Jordaan · Journal of Clinical Ultrasound | Jul 1986 | 864 |
| 14 | Low Heart Rate Variability in a 2-Minute Rhythm Strip Predicts Risk of Coronary Heart Disease and Mortality From Several Causes Joost Dekker, Richard S. Crow, Aaron R. Folsom et al. · Circulation | 12 Sep 2000 | 859 |
| 15 | An open access database for the evaluation of heart sound algorithms Chengyu Liu et al. · Physiological Measurement | 21 Nov 2016 | 833 |
| 16 | Regression Equations for Calculation of Z Scores of Cardiac Structures in a Large Cohort of Healthy Infants, Children, and Adolescents: An Echocardiographic Study Michael D. Pettersen, Wei Du, Mary Ellen Skeens et al. · Journal of the American Society of Echocardiography | 12 Apr 2008 | 803 |
| 17 | Mechanoelectrical Interaction in Tetralogy of Fallot Michael Athanassios Gatzoulis, Jan A. Till, Jane Somerville et al. · Circulation | 15 Jul 1995 | 790 |
| 18 | Ballistocardiography and Seismocardiography: A Review of Recent Advances Omer T. Inan, Pierre‐François Migeotte, Kwangsuk Park et al. · IEEE Journal of Biomedical and Health Informatics | 7 Oct 2014 | 772 |
| 19 | Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography Sarah Leclerc, Erik Smistad, Joao Pedrosa et al. · IEEE Transactions on Medical Imaging | 22 Feb 2019 | 756 |
| 20 | A review of wavelets in biomedical applications Michael A. Unser, Akram Aldroubi · Proceedings of the IEEE | Apr 1996 | 756 |
| 21 | Annotated 12 lead ECG dataset Antônio H. Ribeiro, Ribeiro, Manoel Horta, Gabriela M. M. Paixão et al. · RePEc: Research Papers in Economics | 22 Jan 2020 | 755 |
| 22 | Functional abnormalities in isolated left bundle branch block. The effect of interventricular asynchrony. Cindy L. Grines, Thomas M. Bashore, Harisios K Boudoulas et al. · Circulation | Apr 1989 | 746 |
| 23 | Abnormal Sleep/Wake Cycles and the Effect of Environmental Noise on Sleep Disruption in the Intensive Care Unit Neil S. Freedman, Joost Alexander Christiaan Gazendam, LACHELLE LEVAN et al. · American Journal of Respiratory and Critical Care Medicine | Feb 2001 | 698 |
| 24 | Prognostic Importance of Elevated Jugular Venous Pressure and a Third Heart Sound in Patients with Heart Failure Mark H. Drazner, Jesus Eduardo Rame, Lynne Warner Stevenson et al. · New England Journal of Medicine | 23 Aug 2001 | 666 |
| 25 | Mechanisms Underlying Very-Low-Frequency RR-Interval Oscillations in Humans J. Andrew Taylor, Deborah L. Carr, Christopher W. Myers et al. · Circulation | 11 Aug 1998 | 662 |
| 26 | Multivariate Variational Mode Decomposition Naveed ur Rehman, Hania Aftab · IEEE Transactions on Signal Processing | 4 Nov 2019 | 656 |
| 27 | Transfer Learning with Deep Convolutional Neural Network (CNN) for Pneumonia Detection Using Chest X-ray Tawsifur Rahman, Muhammad E. H. Chowdhury, Amith Abdullah Khandakar et al. · Applied Sciences | 6 May 2020 | 642 |
| 28 | Respiratory Sounds Hans Pasterkamp, Steve S. Kraman, George Robert Wodicka · American Journal of Respiratory and Critical Care Medicine | Sep 1997 | 634 |
| 29 | Arrhythmias documented by 24 hour continuous electrocardiographic monitoring in 50 male medical students without apparent heart disease Michael A. Brodsky, Delon Wu, Pablo Denes et al. · The American Journal of Cardiology | 1977 | 631 |
| 30 | Proposal for International Standardization of the Use of Lung Ultrasound for Patients With COVID ‐19 Gino Soldati, Andrea Smargiassi, Riccardo Inchingolo et al. · Journal of Ultrasound in Medicine | 30 Mar 2020 | 627 |
| 31 | WHO Environmental Noise Guidelines for the European Region: A Systematic Review on Environmental Noise and Cardiovascular and Metabolic Effects: A Summary Elise van Kempen, Maribel Casas, Göran Pershagen et al. · International Journal of Environmental Research and Public Health | 22 Feb 2018 | 626 |
| 32 | A Guide to the Effective Use of Otoacoustic Emissions David T. Kemp, Siobhán Ryan, Peter Bray · Ear and Hearing | Apr 1990 | 624 |
| 33 | COVID-19 Artificial Intelligence Diagnosis Using Only Cough Recordings Jordi Laguarta, Ferran Hueto, Brian Subirana · IEEE Open Journal of Engineering in Medicine and Biology | 2020 | 604 |
| 34 | Requirements for high impact diagnostics in the developing world Mickey S. Urdea, Laura Penny, Stuart S. Olmsted et al. · Nature | Nov 2006 | 604 |
| 35 | Fast and accurate view classification of echocardiograms using deep learning Ali Madani, Ramy Arnaout, Ramy Arnaout (263589) et al. · npj Digital Medicine | 30 Jan 2018 | 595 |
| 36 | Does This Dyspneic Patient in the Emergency Department Have Congestive Heart Failure? Charlie S. Wang · JAMA | 18 Oct 2005 | 595 |
| 37 | Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection Max A Little, Patrick E McSharry, Stephen J Roberts et al. · BioMedical Engineering OnLine | 2007 | 577 |
| 38 | Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network Fei Zhu, Fei Ye, Yuchen Fu et al. · Scientific Reports | May 2019 | 547 |
| 39 | Mel Frequency Cepstral Coefficient and its Applications: A Review Zrar Kh. Abdul, Abdulbasit K. Al‐Talabani · IEEE Access | 2022 | 524 |
| 40 | Logistic Regression-HSMM-based Heart Sound Segmentation David Springer, Lionel Tarassenko, Gari D. Clifford · IEEE Transactions on Biomedical Engineering | 2015 | 524 |
| 41 | Deep learning interpretation of echocardiograms Amirata Ghorbani, David Ouyang, Abubakar Abid et al. · npj Digital Medicine | 24 Jan 2020 | 500 |
| 42 | A Patient-Adapting Heartbeat Classifier Using ECG Morphology and Heartbeat Interval Features Philip de Chazal, Richard B. Reilly · IEEE Transactions on Biomedical Engineering | Dec 2006 | 499 |
| 43 | Systematic review and individual patient data meta-analysis of diagnosis of heart failure, with modelling of implications of different diagnostic strategies in primary care Jonathan Mant, Jenny A Doust, Andrea K. Roalfe et al. · Health Technology Assessment | Jul 2009 | 499 |
| 44 | Acoustically detectable cellular-level lung injury induced by fluid mechanical stresses in microfluidic airway systems Dongeun Huh, Hideki Fujioka, Yi‐Chung Tung et al. · Proceedings of the National Academy of Sciences | 15 Nov 2007 | 495 |
| 45 | Fundamentals of Lung Auscultation Abraham Bohadana, Gabriel Izbicki, Steve S. Kraman · New England Journal of Medicine | 19 Feb 2014 | 485 |
| 46 | Newborn Hearing Screening: The Great Omission Albert L. Mehl, Vickie Thomson · PEDIATRICS | 1998 | 471 |
| 47 | Automated detection and classification of the proximal humerus fracture by using deep learning algorithm Seok Won Chung, Seung Seog Han, Ji Whan Lee et al. · Acta Orthopaedica | 26 Mar 2018 | 464 |
| 48 | Is There a Role for Lung Ultrasound During the COVID ‐19 Pandemic? Gino Soldati, Andrea Smargiassi, Riccardo Inchingolo et al. · Journal of Ultrasound in Medicine | 21 Mar 2020 | 458 |
| 49 | Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data Chloë Brown, Jagmohan Chauhan, Andreas Grammenos et al. | 20 Aug 2020 | 457 |
| 50 | The Relationship of Alterations in Systolic Time Intervals to Ejection Fraction in Patients with Cardiac Disease C. Louis Garrard, Arnold M. Weissler, Harold T. Dodge · Circulation | Sep 1970 | 457 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.