AIMC Topic: Auscultation

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Automated Interpretation of Lung Sounds by Deep Learning in Children With Asthma: Scoping Review and Strengths, Weaknesses, Opportunities, and Threats Analysis.

Journal of medical Internet research
BACKGROUND: The interpretation of lung sounds plays a crucial role in the appropriate diagnosis and management of pediatric asthma. Applying artificial intelligence (AI) to this task has the potential to better standardize assessment and may even imp...

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-...

Identification of Congenital Valvular Murmurs in Young Patients Using Deep Learning-Based Attention Transformers and Phonocardiograms.

IEEE journal of biomedical and health informatics
One in every four newborns suffers from congenital heart disease (CHD) that causes defects in the heart structure. The current gold-standard assessment technique, echocardiography, causes delays in the diagnosis owing to the need for experts who vary...

Improving Valvular Pathologies and Ventricular Dysfunction Diagnostic Efficiency Using Combined Auscultation and Electrocardiography Data: A Multimodal AI Approach.

Sensors (Basel, Switzerland)
Simple sensor-based procedures, including auscultation and electrocardiography (ECG), can facilitate early diagnosis of valvular diseases, resulting in timely treatment. This study assessed the impact of combining these sensor-based procedures with m...

Exploring classical machine learning for identification of pathological lung auscultations.

Computers in biology and medicine
The use of machine learning in biomedical research has surged in recent years thanks to advances in devices and artificial intelligence. Our aim is to expand this body of knowledge by applying machine learning to pulmonary auscultation signals. Despi...

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...

Ensemble Approach on Deep and Handcrafted Features for Neonatal Bowel Sound Detection.

IEEE journal of biomedical and health informatics
For the care of neonatal infants, abdominal auscultation is considered a safe, convenient, and inexpensive method to monitor bowel conditions. With the help of early automated detection of bowel dysfunction, neonatologists could create a diagnosis pl...

Towards fully automated robotic platform for remote auscultation.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Since most developed countries are facing an increase in the number of patients per healthcare worker due to a declining birth rate and an ageing population, relatively simple and safe diagnosis tasks may need to be performed using roboti...

Exploring machine learning for audio-based respiratory condition screening: A concise review of databases, methods, and open issues.

Experimental biology and medicine (Maywood, N.J.)
Auscultation plays an important role in the clinic, and the research community has been exploring machine learning (ML) to enable remote and automatic auscultation for respiratory condition screening via sounds. To give the big picture of what is goi...