Publications citing The CirCor DigiScope Phonocardiogram Dataset v1.0.3

Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods
Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El‐Hafeez et al. Journal Of Big Data, 2024. Cites: dataset, paper

LightCardiacNet: light-weight deep ensemble network with attention mechanism for cardiac sound classification
K V Suma, Deepali Koppad, Dharini Raghavan et al. Systems Science & Control Engineering, 2024. Cites: paper

Phonocardiogram Signal Analysis for Automated Cardiac Murmur Detection
Shivalila Hangaragi, Nizampatnam Neelima. International Conference on Innovations in Communications, Electrical and Computer Engineering (ICICEC), 2024. Cites: dataset

A machine-learning algorithm to grade heart murmurs and stage preclinical myxomatous mitral valve disease in dogs
Andrew McDonald, José Novo Matos, Joel Silva et al. Journal of Veterinary Internal Medicine, 2024. Cites: paper

Enhancing cross-domain robustness in phonocardiogram signal classification using domain-invariant preprocessing and transfer learning
Arnab Maity, Goutam Saha. Computer Methods and Programs in Biomedicine, 2024. Cites: paper

External evaluation of a commercial artificial intelligence-augmented digital auscultation platform in valvular heart disease detection using echocardiography as reference standard
Valentina Roquemen-Echeverri, Peter G. Jacobs, Evan Foster Shalen et al. International Journal of Cardiology, 2024. Cites: paper

Phonocardiogram (PCG) Murmur Detection Based on the Mean Teacher Method
Yi Luo, Zhongtao Fu, Yantian Ding et al. Sensors, 2024. Cites: paper

Enhancement of cardiac and respiratory sounds for cellphone reproduction by means of digital sound processing methods
Maria Belen Echenique, Eduardo Jorge Godoy, Rodrigo F. Cádiz et al. Personal and Ubiquitous Computing, 2024. Cites: paper

Transformers in biosignal analysis: A review
Ayman Anwar, Yassin Khalifa, James L. Coyle et al. Information Fusion, 2024. Cites: paper

FPGA Design of Digital Circuits for Phonocardiogram Pre-Processing Enabling Real-Time and Low-Power AI Processing
Domenico Ragusa, Antonio J. Rodríguez-Almeida, Marco Gazzoni et al. Euromicro Conference on Digital System Design (DSD), 2024. Cites: paper

Low-Power Implementation of a U-Net-based Model for Heart Sound Segmentation on a Low-Cost FPGA
Daniel Enériz, Antonio J. Rodríguez-Almeida, Himar A. Fabelo et al. Euromicro Conference on Digital System Design (DSD), 2024. Cites: paper

Rapid detection and interpretation of heart murmurs using phonocardiograms, transfer learning and explainable artificial intelligence
Fatma Özcan. Health Information Science and Systems, 2024. Cites: paper

A deep neural network approach to heart murmur detection using spectrogram and peak interval features
Soyul Han, Taein Kang, Jungguk Lee et al. Engineering Applications of Artificial Intelligence, 2024. Cites: paper

Heart Murmur Quality Detection Using Deep Neural Networks with Attention Mechanism
Tingwei Wu, Zhaohan Huang, Shilong Li et al. Applied Sciences, 2024. Cites: dataset, paper

Enhancing Heart Murmur Detection: A Comparative Study of Machine Learning Models Utilizing Digital Stethoscopes
Nathaniel Mastracci, Farnaz Derakhshan, Edward R. Sykes et al. IEEE World Conference on Applied Intelligence and Computing (AIC), 2024. Cites: paper

Age-Based Heart Sound Segmentation for Accessible Pediatric Cardiovascular Disease Screening
Ethan Grooby, Yang Yi Poh, Faezeh Marzbanrad. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024. Cites: paper

Exploring Pre-trained General-purpose Audio Representations for Heart Murmur Detection
Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024. Cites: paper

Exploring Wav2vec 2.0 Model for Heart Sound Analysis
Alex Paul Kamson, Akshay Sawant, Prasanta Kumar Ghosh et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024. Cites: paper

Heart Murmur Classification for Diagnostic Applications
Ashley FitzGerald, Taikang Ning. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024. Cites: paper

Towards a Wearable, High Precision, Multi-Functional Stethoscope
Declan Duggan, Volodymyr Sarana, Andreea Factor et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024. Cites: paper

Phonocardiography (PCG) Categorization Using Deep Models
Kaushik Das, Debashish Pal, Madhusudhan Mishra. World Conference on Communication & Computing (WCONF), 2024. Cites: paper

A Comprehensive Survey on Heart Sound Analysis in the Deep Learning Era
Zhao Xu Ren, Yi Chang, Thành Tâm Nguyên et al. IEEE Computational Intelligence Magazine, 2024. Cites: paper

Recognition of Patient Gender: A Machine Learning Preliminary Analysis Using Heart Sounds from Children and Adolescents
Rodrigo Martin Carrillo-Larco. Pediatric Cardiology, 2024. Cites: dataset, paper

An open-access simultaneous electrocardiogram and phonocardiogram database
Arsalan Kazemnejad, Sajjad Karimi, Peiman Gordany et al. Physiological Measurement, 2024. Cites: dataset, paper

Improved recovery of cardiac auscultation sounds using modified cosine transform and LSTM-based masking
Awad Al‐Zaben, Amjad Al-Fahoum, Muhannad J. Ababneh et al. Medical & Biological Engineering & Computing, 2024. Cites: paper

Identifying pediatric heart murmurs and distinguishing innocent from pathologic using deep learning
G. Wayne Zhou, Candace Chien, Justin Chen et al. Artificial Intelligence in Medicine, 2024. Cites: paper

Murmur identification and outcome prediction in phonocardiograms using deep features based on Stockwell transform
Omid Dehghan Manshadi, Sara Mihandoost. Scientific Reports, 2024. Cites: paper

Multiple instance learning framework can facilitate explainability in murmur detection
Maurice Rohr, Benedikt Müller, Sebastian Dill et al. PLOS Digital Health, 2024. Cites: paper

Heart Murmur Severity Stages Classification Using Multikernel Residual CNN
Samarjeet Das, Samarendra Dandapat. IEEE Sensors Journal, 2024. Cites: paper

Intelligent Cardiac Auscultation for Murmur Detection via Parallel-Attentive Models with Uncertainty Estimation
Zixing Zhang, Tao Pang, Jing Han et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2024. Cites: paper

Heart Murmur Classification Using Transfer Learning and Snapshot Ensemble Method
Truc Thi Kim Nguyen, Phuoc Nguyen Duy Vo, Tra Thi Bich Le et al. International Conference on Intelligent Information Technology (ICIIT), 2024. Cites: paper

Exploring new horizons in neuroscience disease detection through innovative visual signal analysis
Nisreen Said Amer, Samir Brahim Belhouari. Scientific Reports, 2024. Cites: paper

A Novel Machine Learning-Based Heart Murmur Detection and Classification using Sound Feature Analysis
Ram Sivaraman, Joe Xiao. International Conference on AI, Machine Learning and Applications (AIMLA), 2024. Cites: dataset, paper

Artificial Intelligence and Pediatrics: Synthetic Knowledge Synthesis
Jernej Završnik, Peter Kokol, Bojan Žlahtič et al. Electronics, 2024. Cites: paper

Identification of Congenital Valvular Murmurs in Young Patients Using Deep Learning-Based Attention Transformers and Phonocardiograms
Mohanad Alkhodari, Leontios J. Hadjileontiadis, Ahsan Habib Khandoker. IEEE Journal of Biomedical and Health Informatics, 2024. Cites: paper

ZCHSound: Open-Source ZJU Paediatric Heart Sound Database With Congenital Heart Disease
Weijie Jia, Yunyan Wang, Renwei Chen et al. IEEE Transactions on Biomedical Engineering, 2024. Cites: paper

Artificial intelligence for heart sound classification: A review
Junxin Chen, Zhihuan Guo, Xu Xu et al. Expert Systems, 2024. Cites: paper

A Comparative Study of Pre-trained Audio and Speech Models for Heart Sound Detection
Yuxin Duan, Chenyu Yang, Zihan Zhao et al. Communications in computer and information science, 2024. Cites: paper

A Noise-Robust Heart Sound Segmentation Algorithm Based on Shannon Energy
Youness Arjoune, Trong Nguyen, Robin Winkler Doroshow et al. IEEE Access, 2024. Cites: paper

Applying Machine Learning Techniques for Multiple Medical Conditions
Mihai-Andrei Costandache. Procedia Computer Science, 2024. Cites: paper

Deep Learning in Heart Sound Analysis: From Techniques to Clinical Applications
Qinghao Zhao, Shijia Geng, Boya Wang et al. Health Data Science, 2024. Cites: paper

Electrocardiogram and Phonocardiogram Signal Data Fusion Using Deep Learning System
Olga Valenzuela, Ignacio Rojas, Peter Glösekötter et al. Lecture notes in computer science, 2024. Cites: paper

Heart Murmur Detection in Phonocardiogram Signals Using Support Vector Machines
Foli Fan, Yuwei Zhang, Chenxi Yang et al. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 2024. Cites: paper

Low-Cost FPGA Implementation of Deep Learning-Based Heart Sound Segmentation for Real-Time CVDs Screening
Daniel Enériz, Antonio J. Rodríguez-Almeida, Himar A. Fabelo et al. IEEE Transactions on Instrumentation and Measurement, 2024. Cites: paper

Machine Learning-Based Intelligent Auscultation Techniques in Congenital Heart Disease: Application and Development
Yang Wang, Xun Yang, Mingtang Ye et al. Congenital Heart Disease, 2024. Cites: paper

Murmur Separation and Classification from Heart Sound
Xiaofu Zhang, Yijing Xia, Saeid Sanei. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 2024. Cites: dataset

E2E Multi-Scale CNN with LSTM for Murmur Detection in PCG or Noise Identification
Alex Paul Kamson, Macline Crecsilla Lewis, B N Vishnu Sunil et al. International Conference on Electrical, Communication, and Computer Engineering (ICECCE), 2023. Cites: paper

Machine Learning Algorithms for Phonocardiogram Signal Classification
Chaitra Nijalingappa, Vps Naidu. International Conference on Communication, Computing and Industry 4.0 (C2I4), 2023. Cites: dataset

An Enhanced Cardiac Auscultation Approach for the detection of abnormal Heartbeat and murmur based on Multimodal Deep Learning
Haseeb Jan, Chen Tang. Research Square, 2023. Cites: paper

Cardiac murmur grading and risk analysis of cardiac diseases based on adaptable heterogeneous-modality multi-task learning
Chenyang Xu, Xin Li, Xinyue Zhang et al. Health Information Science and Systems, 2023. Cites: paper

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