Results 101 to 110 of about 4,324 (198)

An in vitro acoustic analysis and comparison of popular stethoscopes

Medical Devices: Evidence and Research, 2019
Daniel Weiss,1,2 Christine Erie,1,2 Joseph Butera III,2 Ryan Copt,2 Glenn Yeaw,2 Mark Harpster,2 James Hughes,2,3 Deeb N Salem4 1Department of Medicine, Charles E.
Weiss D, Erie C, Butera III J, Copt R, Yeaw G, Harpster M, Hughes J, Salem DN   +7 more
doaj  

High-accuracy lung sound classification for healthy versus unhealthy diagnosis using artificial neural network

Frontiers in Bioengineering and Biotechnology
IntroductionIn recent years, advancements in machine learning and electronic stethoscope technology have enabled high-precision recording and analysis of lung sounds, significantly enhancing pulmonary disease diagnosis.MethodsThis study presents a ...
Weiwei Zhang, Xinyu Li, Qiao Liu, Xiangyang Zheng, Yisu Ge, Xiaotian Pan, Xiaotian Pan, Yu Zhou   +7 more
doaj   +1 more source

Classification of lung sounds using convolutional neural networks

EURASIP Journal on Image and Video Processing, 2017
In the field of medicine, with the introduction of computer systems that can collect and analyze massive amounts of data, many non-invasive diagnostic methods are being developed for a variety of conditions.
Murat Aykanat, Özkan Kılıç, Bahar Kurt, Sevgi Saryal   +3 more
doaj   +1 more source

Can Deep Learning Models Acquire Specialist Knowledge? Identifying Carotid Bruits in Type 2 Diabetes Using an Electronic Stethoscope

IEEE Access
The present study explores the potential of artificial intelligence as a substitute for trained clinician identification of a carotid bruit from multiple auditory recordings from an electronic stethoscope in 98 people with type 2 diabetes, 48 of whom had
Aref Miri Rekavandi, Mohammed Bennamoun, Farid Boussaid, Wendy A. Davis, Timothy M. E. Davis   +4 more
doaj   +1 more source

A machine‐learning algorithm to grade heart murmurs and stage preclinical myxomatous mitral valve disease in dogs

Journal of Veterinary Internal Medicine
Background The presence and intensity of heart murmurs are sensitive indicators of several cardiac diseases in dogs, particularly myxomatous mitral valve disease (MMVD), but accurate interpretation requires substantial clinical expertise.
Andrew McDonald, Jose Novo Matos, Joel Silva, Catheryn Partington, Eve J. Y. Lo, Virginia Luis Fuentes, Lara Barron, Penny Watson, Anurag Agarwal   +8 more
doaj   +1 more source

Learning integrated circuit via electronic stethoscope

Traditional acoustic stethoscopes face limitations in sound amplification and clarity. This project aimed to address these challenges by designing a high-gain and low-noise electronic stethoscope circuit incorporating integrated circuits.
Siu, Wan Yin
core  

The first 200 years of cardiac auscultation and future perspectives

Journal of Multidisciplinary Healthcare, 2019
Maria Rosa Montinari,1 Sergio Minelli2 1Department of Biological and Environmental Science and Technology, University of Salento, Lecce, Italy; 2Department of Cardiology, Local Health Unit Lecce, Lecce, Italy Abstract: Cardiac auscultation – even ...
Montinari MR, Minelli S
doaj  

Evaluation of the electronic stethoscope (FONODOC) as a cardiac screening tool during the preoperative evaluation of children. [PDF]

Indian J Anaesth, 2022
Ahuja V, Kini P, Nileshwar A.
europepmc   +1 more source

Feasibility of Electronic Stethoscope for En Route and Combat Casualty Care

, 2019
In the En Route and Combat Casualty Care environments, occupational stressors can complicate the ability to perform medical interventions which are often used in civilian ground healthcare facilities.
Harding, Charles J., Wilson, Melissa A., Fouts, Brittany L., . US Air Force School of Aerospace Medicine, Aeromedical Research Department, Wright-Patterson AFB, OH.   +3 more
core  

The utility of phonocardiograms in real-time remote cardiac auscultation using an internet-connected electronic stethoscope: Open-label randomized controlled pilot trial. [PDF]

Digit Health, 2023
Hirosawa T, Ito T, Harada Y, Ikenoya K, Yokose M, Shimizu T.   +5 more
europepmc   +1 more source