Infectious Disease

Public Health

Latest AI and machine learning research in public health for healthcare professionals.

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

Understanding cross-domain traffic scenarios from multicamera surveillance network is important for ...

Overground robotic training effects on walking and secondary health conditions in individuals with spinal cord injury: systematic review.

Overground powered lower limb exoskeletons (EXOs) have proven to be valid devices in gait rehabilita...

Efficient Violence Detection in Surveillance.

Intelligent video surveillance systems are rapidly being introduced to public places. The adoption o...

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 c...

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 re...

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 show...

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...

Deep-learning model for predicting the survival of rectal adenocarcinoma patients based on a surveillance, epidemiology, and end results analysis.

BACKGROUND: We collected information on patients with rectal adenocarcinoma in the United States fro...

Proposing a novel deep network for detecting COVID-19 based on chest images.

The rapid outbreak of coronavirus threatens humans' life all around the world. Due to the insufficie...

Deep learning forecasting using time-varying parameters of the SIRD model for Covid-19.

Accurate epidemiological models are necessary for governments, organizations, and individuals to res...

A Machine Learning Pipeline for Accurate COVID-19 Health Outcome Prediction using Longitudinal Electronic Health Records.

Current COVID-19 predictive models primarily focus on predicting the risk of mortality, and rely on ...

Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools.

Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on s...

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots.

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiolo...

Analyzing the Effect of Vaccination Over COVID Cases and Deaths in Asian Countries Using Machine Learning Models.

Coronavirus Disease 2019 (COVID-19) is spreading across the world, and vaccinations are running para...

Enabling CT-Scans for covid detection using transfer learning-based neural networks.

Today, we are coping with the pandemic, and the novel virus is covertly evolving day by day. Therefo...

Spatiotemporal sentiment variation analysis of geotagged COVID-19 tweets from India using a hybrid deep learning model.

India is a hotspot of the COVID-19 crisis. During the first wave, several lockdowns (L) and gradual ...

WEENet: An Intelligent System for Diagnosing COVID-19 and Lung Cancer in IoMT Environments.

The coronavirus disease 2019 (COVID-19) pandemic has caused a major outbreak around the world with s...

A deep learning method for cyanobacterial harmful algae blooms prediction in Taihu Lake, China.

Cyanobacterial Harmful Algae Blooms (CyanoHABs) in the eutrophic lakes have become a global environm...

Natural language processing for automated surveillance of intraoperative neuromonitoring in spine surgery.

We sought to develop natural language processing (NLP) methods for automated detection and character...

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