Results 171 to 180 of about 29,039 (221)

Heart murmurs in the general population: diagnostic value and prevalence from the Tromsø Study. [PDF]

Heart
Davidsen AH, Andersen S, Halvorsen PA, Aviles Solis JC, Schirmer H, Melbye H.   +5 more
europepmc   +1 more source

Clinical Applications and Mathematical Models of Bowel Sounds. [PDF]

Biomedicines
Geng W, Cao X, Liao W, Yang Y.
europepmc   +1 more source

A dataset of heart sound regurgitation of patients with heart valve disorders. [PDF]

Data Brief
Fraiwan M, Ibnian A, Haider NS.
europepmc   +1 more source

A Robust and Efficient Workflow for Heart Valve Disease Detection from PCG Signals: Integrating WCNN, MFCC Optimization, and Signal Quality Evaluation. [PDF]

Sensors (Basel)
Lai SC, Chang YC, Hung YH, Wang ST, Liang YF, Hsu LC, Sheu MH, Chang CY.   +7 more
europepmc   +1 more source

Identification of adventitious lung sounds in children with respiratory illnesses in Bangladesh using Artificial Intelligence and Digital Auscultation

Ahmed S, Khan AM, Nair H, Cunningham S, McLane IM, Islam MS, Islam AA, Tabassum R, Chowdhury NH, Sultana N, Githinji L, Justin MM, Jahan I, Wahiduzzaman M, Mitra DK, Hasan MK, Chowdhury MZR, Shahidullah M, Baqui AH, McCollum ED.   +19 more
europepmc   +1 more source

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Automatic pediatric congenital heart disease classification based on heart sound signal

Artificial Intelligence in Medicine, 2022
Congenital heart diseases (CHD) are the most common birth defects, and the early diagnosis of CHD is crucial for CHD therapy. However, there are relatively few studies on intelligent auscultation for pediatric CHD, due to the fact that effective cooperation of the patient is required for the acquisition of useable heart sounds by electronic ...
Weize, Xu, Kai, Yu, Jingjing, Ye, Haomin, Li, Jiajia, Chen, Fei, Yin, Jingfang, Xu, Jihua, Zhu, Die, Li, Qiang, Shu   +9 more
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Heart Sound Classification based on Residual Shrinkage Networks

2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022
Heart sound classification is one of the non-invasive methods for early detection of the cardiovascular diseases (CVDs), the leading cause for deaths. In recent years, Computer Audition (CA) technology has become increasingly sophisticated, auxiliary diagnosis technology of heart disease based on CA has become a popular research area.
Zhu, Lixian, Qian, Kun, Wang, Zhihua, Hu, Bin, Yamamoto, Yoshiharu, Schuller, Björn W.   +5 more
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A Federated Learning Paradigm for Heart Sound Classification

2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022
Cardiovascular diseases (CVDs) have been ranked as the leading cause for deaths. The early diagnosis of CVDs is a crucial task in the medical practice. A plethora of efforts were given to the automated auscultation of heart sound, which leverages the power of computer audition to develop a cheap, non-invasive method that can be used at any time and ...
Qiu, Wanyong, Qian, Kun, Wang, Zhihua, Chang, Yi, Bao, Zhihao, Hu, Bin, Schuller, Bjorn W., Yamamoto, Yoshiharu   +7 more
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Heart Sound Classification using Deep Learning

2023 8th International Conference on Smart and Sustainable Technologies (SpliTech), 2023
Cardiac auscultation is the process of listening to the sounds of the heart with a stethoscope, which can provide important diagnostic information about a patient’s heart function. It is a key component of a physical examination and can help doctors identify potential heart problems such as murmurs, arrhythmias, and valve disorders. Deep learning-based
Marija Habijan, Irena Galić, Aleksandra Pizurica   +2 more
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Heart sound classification using the SNMFNet classifier

Physiological Measurement, 2019
Heart sound classification still suffers from the challenges involved in achieving high accuracy in the case of small samples. Dimension reduction attempts to extract low-dimensional features with more discriminability from high-dimensional spaces or raw data, and is popular in learning predictive models that target small sample problems.
Wei, Han, Shengli, Xie, Zuyuan, Yang, Songbin, Zhou, Haonan, Huang   +4 more
openaire   +2 more sources