The main goal of this paper is to develop a classification model and a technique to identify
bronchiolitis and bronchiectasis using lung sound analysis. In this paper, we develop a …

In settings requiring synthetic data generation based on a clinical cohort, eg, due to data
protection regulations, heterogeneity across individuals might be a nuisance that we need to …

This thesis explores the use of deep neural networks for sound event detection in the
medical industry. Specifically, the goal is to to detect the ongoing ventilation on newborn …

This paper aims at analyzing the performance of reinforcement learning (RL) agents when
trained in environments created by a generative adversarial network (GAN). This is a first …

Respiratory diseases are a major global health concern, with millions of people suffering
from disorders such as asthma, bronchitis, chronic obstructive pulmonary disease (COPD) …

Data augmentation plays a pivotal role in enhancing the performance of machine learning
models, particularly in tasks where labeled data is limited. This paper introduces an …

Since the COVID-19 outbreak, major scientific effort has been done by researchers and
companies worldwide to develop a digital diagnostic tool to screen this disease through …

Perception or imagination requires top-down signals from high-level cortex to primary visual
cortex (V1) to reconstruct or simulate the representations bottom-up stimulated by the seen …

Abstract Background and Objective Respiratory Diseases are one of the leading chronic
illnesses in the world according to the reports by World Health Organization. Diagnosing …

Due to the data shortage problem, which is one of the major problems in the field of machine
learning, the accuracy level of many applications remains well below the expected. It …