[HTML][HTML] Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews

A Martinez-Millana, A Saez-Saez… - International Journal of …, 2022 - Elsevier
Background Artificial intelligence is fueling a new revolution in medicine and in the
healthcare sector. Despite the growing evidence on the benefits of artificial intelligence there …

[HTML][HTML] Detection of pneumonia using convolutional neural networks and deep learning

P Szepesi, L Szilágyi - Biocybernetics and biomedical engineering, 2022 - Elsevier
The objective and automated detection of pneumonia represents a serious challenge in
medical imaging, because the signs of the illness are not obvious in CT or X-ray scans …

[HTML][HTML] Deep learning for pneumonia detection in chest x-ray images: A comprehensive survey

R Siddiqi, S Javaid - Journal of imaging, 2024 - mdpi.com
This paper addresses the significant problem of identifying the relevant background and
contextual literature related to deep learning (DL) as an evolving technology in order to …

Infant birth weight estimation and low birth weight classification in United Arab Emirates using machine learning algorithms

W Khan, N Zaki, MM Masud, A Ahmad, L Ali, N Ali… - Scientific reports, 2022 - nature.com
Accurate prediction of a newborn's birth weight (BW) is a crucial determinant to evaluate the
newborn's health and safety. Infants with low BW (LBW) are at a higher risk of serious short …

Design ensemble deep learning model for pneumonia disease classification

K El Asnaoui - International Journal of Multimedia Information …, 2021 - Springer
With the recent spread of the SARS-CoV-2 virus, computer-aided diagnosis (CAD) has
received more attention. The most important CAD application is to detect and classify …

A deep convolutional neural network for pneumonia detection in x-ray images with attention ensemble

Q An, W Chen, W Shao - Diagnostics, 2024 - mdpi.com
In the domain of AI-driven healthcare, deep learning models have markedly advanced
pneumonia diagnosis through X-ray image analysis, thus indicating a significant stride in the …

Pneumonia detection on chest x-ray using radiomic features and contrastive learning

Y Han, C Chen, A Tewfik, Y Ding… - 2021 IEEE 18th …, 2021 - ieeexplore.ieee.org
Chest X-ray becomes one of the most common medical diagnoses due to its
noninvasiveness. The number of chest X-ray images has skyrocketed, but reading chest X …

M Tac: A Multispectral Multimodal Visuotactile Sensor with Beyond-Human Sensory Capabilities

S Li, H Yu, G Pan, H Tang, J Zhang, L Ye… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
To realize the exquisite interaction and precise manipulation for the robot, in this article, we
propose a multispectral multimodal visuotactile sensor named M Tac, which combines …

Review on chest pathogies detection systems using deep learning techniques

A Rehman, A Khan, G Fatima, S Naz… - Artificial Intelligence …, 2023 - Springer
Chest radiography is the standard and most affordable way to diagnose, analyze, and
examine different thoracic and chest diseases. Typically, the radiograph is examined by an …

Pneumonia detection from lung X‐ray images using local search aided sine cosine algorithm based deep feature selection method

S Chattopadhyay, R Kundu, PK Singh… - … Journal of Intelligent …, 2022 - Wiley Online Library
Pneumonia is a major cause of death among children below the age of 5 years, globally. It is
especially prevalent in develo** and underdeveloped nations where the risk factors for …