ReviewBioMed research international2020
A Review of Computer-Aided Heart Sound Detection Techniques.
Review in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A review on deep learning methods for heart sound signal analysis.Frontiers in artificial intelligence · 2024Pooled it
- The Utility of Real-Time Remote Auscultation Using a Bluetooth-Connected Electronic Stethoscope: Open-Label Randomized Controlled Pilot Trial.JMIR mHealth and uHealth · 2021Trial
- Enhancing pediatric cardiac auscultation with data-driven murmur detection: toward tele-consultation applications.Pediatric research · 2026Article
- Advancing cardiovascular screening: deep learning-based heart-sound classification using SMOTE and temporal modeling.Scientific reports · 2026Article
- [A study on heart sound classification algorithm based on improved Mel-frequency cepstrum coefficient feature extraction and deep Transformer].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Article
- Heart Sound Classification Based on Multi-Scale Feature Fusion and Channel Attention Module.Bioengineering (Basel, Switzerland) · 2025Article
- The heart sound classification of congenital heart disease by using median EEMD-Hurst and threshold denoising method.Medical & biological engineering & computing · 2025Article
- A progressive attention-based cross-modal fusion network for cardiovascular disease detection using synchronized electrocardiogram and phonocardiogram signals.PeerJ. Computer science · 2025Article
- [Heart sound classification algorithm based on bispectral feature extraction and convolutional neural networks].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024Article
- Computer-Aided Lung Auscultation Screening and Radiographic Evaluation of Pediatric Pneumonia.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2024Article
- Accurate Localization of First and Second Heart Sounds via Template Matching in Forcecardiography Signals.Sensors (Basel, Switzerland) · 2024Article
- Federated Abnormal Heart Sound Detection with Weak to No Labels.Cyborg and bionic systems (Washington, D.C.) · 2024Article
- Deep Learning in Heart Sound Analysis: From Techniques to Clinical Applications.Health data science · 2024Review
- Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review.Bioengineering (Basel, Switzerland) · 2023Review
- Classifying Heart-Sound Signals Based on CNN Trained on MelSpectrum and Log-MelSpectrum Features.Bioengineering (Basel, Switzerland) · 2023Article
- A feasible approach to smart remote health monitoring: Subscription-based model.Frontiers in public health · 2023Article
- A Computer-Aided Heart Valve Disease Diagnosis System Based on Machine Learning.Journal of healthcare engineering · 2023Article
- Construction and validation of a method for automated time label segmentation of heart sounds.Frontiers in artificial intelligence · 2023Article
- Evaluation of the electronic stethoscope (FONODOC) as a cardiac screening tool during the preoperative evaluation of children.Indian journal of anaesthesia · 2022Article
- Transfer Learning Models for Detecting Six Categories of Phonocardiogram Recordings.Journal of cardiovascular development and disease · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular diseases have become one of the most prevalent threats to human health throughout the world. As a noninvasive assistant diagnostic tool, the heart sound detection techniques play an important role in the prediction of cardiovascular diseases. In this paper, the latest development of the computer-aided heart sound detection techniques over the last five years has been reviewed. There are mainly the following aspects: the theories of heart sounds and the relationship between heart sounds and cardiovascular diseases; the key technologies used in the processing and analysis of heart sound signals, including denoising, segmentation, feature extraction and classification; with emphasis, the applications of deep learning algorithm in heart sound processing. In the end, some areas for future research in computer-aided heart sound detection techniques are explored, hoping to provide reference to the prediction of cardiovascular diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.