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Auscultation

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Enhancing bowel sound recognition with self-attention and self-supervised pre-training.

PloS one
Bowel sounds, a reflection of the gastrointestinal tract's peristalsis, are essential for diagnosing and monitoring gastrointestinal conditions. However, the absence of an effective, non-invasive method for assessing digestion through auscultation ha...

Elevating Patient Care With Deep Learning: High-Resolution Cervical Auscultation Signals for Swallowing Kinematic Analysis in Nasogastric Tube Patients.

IEEE journal of translational engineering in health and medicine
Patients with nasogastric (NG) tubes require careful monitoring due to the potential impact of the tube on their ability to swallow safely. This study aimed to investigate the utility of high-resolution cervical auscultation (HRCA) signals in assessi...

Swallowing Assessment using High-Resolution Cervical Auscultations and Transformer-based Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Swallowing assessment is a crucial task to reveal swallowing abnormalities. There are multiple modalities to analyze swallowing kinematics, such as videofluoroscopic swallow studies (VFSS), which is the gold standard method, and high-resolution cervi...

Towards Non-Invasive Swallowing Assessment: an AI-Powered Interface for Swallowing Kinematic Analysis using High-Resolution Cervical Auscultation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Swallowing is a pivotal physiological function for human sustenance and hydration. Dysfunctions, termed dysphagia, necessitate prompt and precise diagnosis. Videofluoroscopic swallowing studies (VFSS) remain the gold standard for swallowing assessmen...

Development and internal validation of an artificial intelligence-assisted bowel sounds auscultation system to predict early enteral nutrition-associated diarrhoea in acute pancreatitis: a prospective observational study.

British journal of hospital medicine (London, England : 2005)
An artificial intelligence-assisted prediction model for enteral nutrition-associated diarrhoea (ENAD) in acute pancreatitis (AP) was developed utilising data obtained from bowel sounds auscultation. This model underwent validation through a single-...

[Bowel Sounds Detection Method Based on ResNet-BiLSTM and Attention Mechanism].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Bowel sounds can reflect the movement and health status of the gastrointestinal tract. However, the traditional manual auscultation method has subjective deviation and is time-consuming and labor-intensive. In order to better assist doctors in diagno...

[Artificial intelligence and machine learning in auscultation: prospects of the project DigitaLung].

Pneumologie (Stuttgart, Germany)
Auscultation is one of the key medical skills in physical examination. The main problem with auscultation is the lack of objectivity of the findings and great dependence on the experience of the examiner. Auscultation using machine learning and neura...

An explainable and accurate transformer-based deep learning model for wheeze classification utilizing real-world pediatric data.

Scientific reports
Auscultation is a method that involves listening to sounds from the patient's body, mainly using a stethoscope, to diagnose diseases. The stethoscope allows for non-invasive, real-time diagnosis, and it is ideal for diagnosing respiratory diseases an...

A MEMS seismometer respiratory monitor for work of breathing assessment and adventitious lung sounds detection via deep learning.

Scientific reports
Physicians evaluate a patient's respiratory health during a physical examination by visual assessment of the work of breathing (WoB) to determine respiratory stability, and by detecting abnormal lung sounds via lung auscultation using a stethoscope t...

Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Pediatric respiratory diseases, including asthma and pneumonia, are major causes of morbidity and mortality in children. Auscultation of lung sounds is a key diagnostic tool but is prone to subjective variability. The integration of artif...