The aim of this systematic literature review (SLR) is to identify and critically evaluate current
research advancements with respect to small data and the use of data augmentation …

Recently, assistive explanations for difficulties in the health check area have been made
viable thanks in considerable portion to technologies like deep learning and machine …

Abstract Background: The World Health Organization (WHO) establishes as a top priority the
early detection of respiratory diseases. This detection could be performed by means of …

This paper proposes a serial hardware architecture of a multilayer perceptron (MLP) neural
network for real-time wheezing detection in respiratory sounds. As an established …

The use of computer-based automated approaches and improvements in lung sound
recording techniques have made lung sound-based diagnostics even better and devoid of …

Early identification of respiratory irregularities is critical for improving lung health and
reducing global mortality rates. The analysis of respiratory sounds plays a significant role in …

Abstract Machine learning methods for classifying respiratory anomalies have provided low
classification accuracy. So high classification accuracy is required in order to utilize …

Wheeze and crackle analysis are important parameters helpful in the clinical diagnosis of
respiratory diseases. With the advent of deep learning techniques, objective medical …

The detection of abnormal breath sounds with a stethoscope is important for diagnosing
respiratory diseases and providing first aid. However, accurate interpretation of breath …

The aim of this systematic literature review (SLR) is to identify and critically evaluate current
research advancements with respect to small data and the use of data augmentation …