Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review

M Khan, MT Mehran, ZU Haq, Z Ullah, SR Naqvi… - Expert systems with …, 2021 - Elsevier
During the current global public health emergency caused by novel coronavirus disease 19
(COVID-19), researchers and medical experts started working day and night to search for …

An explainable artificial intelligence software system for predicting diabetes

PN Srinivasu, S Ahmed, M Hassaballah, N Almusallam - Heliyon, 2024 - cell.com
Implementing diabetes surveillance systems is paramount to mitigate the risk of incurring
substantial medical expenses. Currently, blood glucose is measured by minimally invasive …

CNN Models Using Chest X-Ray Images for COVID-19 Detection: A Survey.

N Mellal, S Zaidi - Revue d'Intelligence Artificielle, 2023 - search.ebscohost.com
The COVID-19 pandemic, which began in 2019, has spread globally, causing substantial
human suffering and economic disruption. A collaborative global effort is essential to combat …

Deep Learning-Based Red Blood Cell Classification for Sickle Cell Anemia Diagnosis Using Hybrid CNN-LSTM Model.

A Deo, I Pandey, SS Khan, A Mandlik… - Traitement du …, 2024 - search.ebscohost.com
A mutation in the beta-globin gene results in the blood condition known as Sickle cell
anemia. It is estimated that number of individuals affected by sickle cell anemia worldwide …

[PDF][PDF] Enhanced Disease Detection Using Contrast Limited Adaptive Histogram Equalization and Multi-Objective Cuckoo Search in Deep Learning

H Çiğ, MT Güllüoğlu, MB Er, U Kuran… - Traitement Du …, 2023 - researchgate.net
Accepted: 5 May 2023 Delayed diagnosis of numerous diseases often results in postponed
treatment, adversely affecting patient outcomes. By analyzing biological signals and patient …

[PDF][PDF] Sentiment analysis of electronic social media based on deep learning

VD Derbentsev, VS Bezkorovainyi, AV Matviychuk… - no. M3e2, 2023 - ds.knu.edu.ua
This paper describes Deep Learning approach of sentiment analyses which is an active
research subject in the domain of Natural Language Processing. For this purpose we have …

AI-based user authentication reinforcement by continuous extraction of behavioral interaction features

D Garabato, C Dafonte, R Santovena, A Silvelo… - Neural Computing and …, 2022 - Springer
In this work, we conduct an experiment to analyze the feasibility of a continuous
authentication method based on the monitorization of the users' activity to verify their …

Computer tomography image based interconnected antecedence clustering model using deep convolution neural network for prediction of COVID-19

SK Santhi - Traitement du Signal, 2023 - ir.vignan.ac.in
The sudden appearance of the COVID-19 pandemic as a major health threat is a serious
concern for global health professionals. The world's most pressing problem has now been …

An effective medical image classification: transfer learning enhanced by auto encoder and classified with SVM

Ö Sevinç, M Mehrubeoglu, M Güzel… - Traitement du …, 2022 - avesis.omu.edu.tr
The count of white blood cells is vital for disease diagnosis, which is exploited to identify
many diseases like infections and leukemia. COVID-19 is another critical disease which …

A deep learning framework for automated and generalized synaptic event analysis

PS O'Neill, M Baccino-Calace, P Rupprecht, S Lee… - bioRxiv, 2023 - biorxiv.org
Quantitative information about synaptic transmission is key to our understanding of neural
function. Spontaneously occurring synaptic events carry fundamental information about …