The past 5 years have seen an explosion of interest in the use of artificial intelligence (AI) and machine learning techniques in medicine. This has been driven by the development of …
In this study, accurate and convenient prediction models of tubular solar still performance, expressed as hourly production, were developed by utilizing machine learning. Based on …
This work introduces a complete study of freshwater productivity prediction of a solar-driven humidification-dehumidification unit (HDH) based on experimental and machine learning …
F Vaquerizo-Villar, D Álvarez… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
This study aims at assessing the usefulness of deep learning to enhance the diagnostic ability of oximetry in the context of automated detection of pediatric obstructive sleep apnea …
The gold standard approach to diagnose obstructive sleep apnea (OSA) in children is overnight in-lab polysomnography (PSG), which is labor-intensive for clinicians and onerous …
D Zhang, Y Ma, J Xu, F Yi - Medicine, 2022 - journals.lww.com
Background: Refractory hypoxemia episodes are characteristic of obstructive sleep apnea (OSA). Patients with OSA suffer from oxidative stress in all systems. Atrial fibrillation (AF) is a …
G Bazoukis, SC Bollepalli, CT Chung, X Li… - Journal of Clinical …, 2023 - jcsm.aasm.org
Study Objectives: Machine learning (ML) models have been employed in the setting of sleep disorders. This review aims to summarize the existing data about the role of ML techniques …
G Zhang, L Luo, L Zhang, Z Liu - Diagnostics, 2023 - mdpi.com
Machine Learning (ML) is an algorithm based on big data, which learns patterns from the previously observed data through classifying, predicting, and optimizing to accomplish …
G Korompili, A Amfilochiou, L Kokkalas, SA Mitilineos… - Scientific data, 2021 - nature.com
The sleep apnea syndrome is a chronic condition that affects the quality of life and increases the risk of severe health conditions such as cardiovascular diseases. However, the …