ArticleBiological cybernetics1992
Noninvasive diagnosis of coronary artery disease using a neural network algorithm.
Article in Biological cybernetics, 1992. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 64 citations in OpenAlex.
- Coronary artery disease diagnosis with signal processing and machine learning of heart sound signals: a systematic review.NPJ digital medicine · 2026Article
- AI-Based Detection of Coronary Artery Occlusion Using Acoustic Biomarkers Before and After Stent Placement.IEEE open journal of engineering in medicine and biology · 2025Article
- Differential disease diagnoses of epistaxis based on dynamic uncertain causality graph.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2023Article
- The Efficacy of Machine-Learning-Supported Smart System for Heart Disease Prediction.Healthcare (Basel, Switzerland) · 2022Article
- FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model.Frontiers in medical technology · 2021Article
- Artificial intelligence to predict needs for urgent revascularization from 12-leads electrocardiography in emergency patients.PloS one · 2019Article
- The clinical evaluation of the CADence device in the acoustic detection of coronary artery disease.The international journal of cardiovascular imaging · 2018Article
- Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis.Journal of healthcare engineering · 2017Article
- Cardiovascular risk prediction: a comparative study of Framingham and quantum neural network based approach.Patient preference and adherence · 2016Article
- Data-Mining-Based Coronary Heart Disease Risk Prediction Model Using Fuzzy Logic and Decision Tree.Healthcare informatics research · 2015Article
- Design of a fuzzy-based decision support system for coronary heart disease diagnosis.Journal of medical systems · 2012Article
- Cryptococcus neoformans chemotyping by quantitative analysis of 1H nuclear magnetic resonance spectra of glucuronoxylomannans with a computer-simulated artificial neural network.Clinical and diagnostic laboratory immunology · 1998Article
- A feed forward neural network for classification of bull's-eye myocardial perfusion images.European journal of nuclear medicine · 1995Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study examines the utility of neural networks for detecting coronary artery disease noninvasively by using the clinical examination variables and extracting useful information from the diastolic heart sounds associated with coronary occlusions. It has been widely reported that coronary stenoses produce sounds due to the turbulent blood flow in these vessels. These complex and highly attenuated signals taken from recordings made in both soundproof and noisy rooms were detected and analyzed to provide feature set based on the poles and power spectral density function (PSD) of the Autoregressive (AR) method after Adaptive Line Enhancement (ALE) method. In addition, some physical examination variables such as sex, age, body weight, smoking condition, diastolic pressure, systolic pressure and derivation from them were included in the feature vector. This feature vector was used as the input pattern to the neural network. The analysis was studied on one hundred recordings (63 abnormal, 37 normals). The network correctly identified 84% of the subjects with coronary artery disease and 89% of the normal subjects.
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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.