AIMC Topic: Stethoscopes

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StethAid: A Digital Auscultation Platform for Pediatrics.

Sensors (Basel, Switzerland)
(1) Background: Mastery of auscultation can be challenging for many healthcare providers. Artificial intelligence (AI)-powered digital support is emerging as an aid to assist with the interpretation of auscultated sounds. A few AI-augmented digital s...

Design of ear-contactless stethoscope and improvement in the performance of deep learning based on CNN to classify the heart sound.

Medical & biological engineering & computing
Cardiac-related disorders are rapidly growing throughout the world. Accurate classification of cardiovascular diseases is an important research topic in healthcare. During COVID-19, auscultating heart sounds was challenging as health workers and doct...

Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study.

The Lancet. Digital health
BACKGROUND: Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is despite previous presentations to primary care with symptoms. We aim...

Deep Learning Algorithm for Automated Cardiac Murmur Detection via a Digital Stethoscope Platform.

Journal of the American Heart Association
Background Clinicians vary markedly in their ability to detect murmurs during cardiac auscultation and identify the underlying pathological features. Deep learning approaches have shown promise in medicine by transforming collected data into clinical...

Hemopneumothorax detection through the process of artificial evolution - a feasibility study.

Military Medical Research
BACKGROUND: Tension pneumothorax is one of the leading causes of preventable death on the battlefield. Current prehospital diagnosis relies on a subjective clinical impression complemented by a manual thoracic and respiratory examination. These techn...

Artificial intelligence accuracy in detecting pathological breath sounds in children using digital stethoscopes.

Respiratory research
BACKGROUND: Manual auscultation to detect abnormal breath sounds has poor inter-observer reliability. Digital stethoscopes with artificial intelligence (AI) could improve reliable detection of these sounds. We aimed to independently test the abilitie...

A novel deep learning based automatic auscultatory method to measure blood pressure.

International journal of medical informatics
BACKGROUND: It is clinically important to develop innovative techniques that can accurately measure blood pressures (BP) automatically.

Practical implementation of artificial intelligence algorithms in pulmonary auscultation examination.

European journal of pediatrics
Lung auscultation is an important part of a physical examination. However, its biggest drawback is its subjectivity. The results depend on the experience and ability of the doctor to perceive and distinguish pathologies in sounds heard via a stethosc...

A novel feature extraction technique for pulmonary sound analysis based on EMD.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The stethoscope based auscultation technique is a primary diagnostic tool for chest sound analysis. However, the performance of this method is limited due to its dependency on physicians experience, knowledge and also clarit...

AI-powered digital stethoscopes: A new opportunity in tuberculosis screening?

Med (New York, N.Y.)
Tuberculosis screening faces challenges of under-detection, costly approaches, and inequitable access. AI-enabled digital stethoscopes have demonstrated promising accuracy and feasibility for detecting lung and cardiovascular abnormalities, with prom...