Public Health

Predicting diarrhoea outbreaks with climate change.

BACKGROUND: Climate change is expected to exacerbate diarrhoea outbreaks across the developing world, most notably in Sub-Saharan countries such as South Africa. In South Africa, diseases related to diarrhoea outbreak is a leading cause of morbidity and mortality. In this study, we modelled the impacts of climate change on diarrhoea with various machine learning (ML) methods to predict daily outbr...

Deep learning time series prediction models in surveillance data of hepatitis incidence in China.

BACKGROUND: Precise incidence prediction of Hepatitis infectious disease is critical for early prevention and better government strategic planning. In this paper, we presented different prediction models using deep learning methods based on the monthly incidence of Hepatitis through a national public health surveillance system in China mainland.

Detection of COVID-19 from CT and Chest X-ray Images Using Deep Learning Models.

Coronavirus 2019 (COVID-19) is a highly transmissible and pathogenic virus caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), which fir...

A hybrid resampling algorithms SMOTE and ENN based deep learning models for identification of Marburg virus inhibitors.

Marburg virus (MARV) is a sporadic outbreak of a zoonotic disease that causes lethal hemorrhagic fever in humans. We propose a deep learning model wi...

A Real-Time Crowd Monitoring and Management System for Social Distance Classification and Healthcare Using Deep Learning.

Coronavirus born COVID-19 disease has spread its roots in the whole world. It is primarily spread by physical contact. As a preventive measure, proper...

Vision Transformer and Deep Sequence Learning for Human Activity Recognition in Surveillance Videos.

Human Activity Recognition is an active research area with several Convolutional Neural Network (CNN) based features extraction and classification met...

Computational and Mathematical Methods in Medicine Prediction of COVID-19 in BRICS Countries: An Integrated Deep Learning Model of CEEMDAN-R-ILSTM-Elman.

Since the outbreak of COVID-19, BRICS countries have experienced different epidemic spread due to different health conditions, social isolation measur...

Evaluation of the humoral response induced by BBIBP-CorV vaccine by determining neutralizing antibodies in peruvian healthcare personnel.

OBJECTIVE.: To determine the titer of antibodies against the receptor binding domain (RBD) of the spike protein (S) in health personnel between the 4t...

Automated System for Identifying COVID-19 Infections in Computed Tomography Images Using Deep Learning Models.

Coronavirus disease 2019 (COVID-19) is a novel disease that affects healthcare on a global scale and cannot be ignored because of its high fatality ra...

Intelligent Wearable Devices Enabled Automatic Vehicle Detection and Tracking System with Video-Enabled UAV Networks Using Deep Convolutional Neural Network and IoT Surveillance.

The discipline of computer vision is becoming more popular as a research subject. In a surveillance-based computer vision application, item identifica...

Epidemiological predictive modeling: lessons learned from the Kuopio ischemic heart disease risk factor study.

PURPOSE: The use of predictive models in epidemiology is relatively narrow as most of the studies report results of traditional statistical models suc...

Deep Learning Based SWIR Object Detection in Long-Range Surveillance Systems: An Automated Cross-Spectral Approach.

SWIR imaging bears considerable advantages over visible-light (color) and thermal images in certain challenging propagation conditions. Thus, the SWIR...

[Usage of Artificial Intelligence in the Combat against the COVID-19 Pandemic].

The COVID-19 pandemic is a global health emergency of historic dimension. In this situation, researchers worldwide wanted to help manage the pandemic ...

Vaxi-DL: A web-based deep learning server to identify potential vaccine candidates.

The development of a new vaccine is a challenging exercise involving several steps including computational studies, experimental work, and animal stud...

Cross-Domain Traffic Scene Understanding by Integrating Deep Learning and Topic Model.

Understanding cross-domain traffic scenarios from multicamera surveillance network is important for environmental perception. Most of existing methods...

Efficient Violence Detection in Surveillance.

Intelligent video surveillance systems are rapidly being introduced to public places. The adoption of computer vision and machine learning techniques ...

A Survey of Underwater Acoustic Data Classification Methods Using Deep Learning for Shoreline Surveillance.

This paper presents a comprehensive overview of current deep-learning methods for automatic object classification of underwater sonar data for shoreli...

Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany.

During 2020, the infection rate of COVID-19 has been investigated by many scholars from different research fields. In this context, reliable and inter...

COVID-19 Identification System Using Transfer Learning Technique With Mobile-NetV2 and Chest X-Ray Images.

Diagnosis is a crucial precautionary step in research studies of the coronavirus disease, which shows indications similar to those of various pneumoni...

Study of Different Deep Learning Methods for Coronavirus (COVID-19) Pandemic: Taxonomy, Survey and Insights.

COVID-19 has evolved into one of the most severe and acute illnesses. The number of deaths continues to climb despite the development of vaccines and ...