Public Health

GACDN: generative adversarial feature completion and diagnosis network for COVID-19.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) causes tens of million infection world-wide. Many machine learning methods have been proposed for the computer-aided diagnosis between COVID-19 and community-acquired pneumonia (CAP) from chest computed tomography (CT) images. Most of these methods utilized the location-specific handcrafted features based on the segmentation results t...

What influences attitudes about artificial intelligence adoption: Evidence from U.S. local officials.

Rapid advances in machine learning and related techniques have increased optimism about self-driving cars, autonomous surgery, and other uses of artificial intelligence (AI). But adoption of these technologies is not simply a matter of breakthroughs in the design and training of algorithms. Regulators around the world will have to make a litany of choices about law and policy surrounding AI. To ad...

Early prediction of in-hospital death of COVID-19 patients: a machine-learning model based on age, blood analyses, and chest x-ray score.

An early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED) was developed and validated ...

Public Perception and Reception of Robotic Applications in Public Health Emergencies Based on a Questionnaire Survey Conducted during COVID-19.

Various intelligent technologies have been applied during COVID-19, which has become a worldwide public health emergency and brought significant chall...

Development of monoclonal antibodies for quantification of bovine tumor necrosis factor-α.

The expression of the proinflammatory cytokine tumor necrosis factor-α (TNF-α) is associated with production losses in dairy cows and is a hallmark of...

Machine learning and artificial intelligence: applications in healthcare epidemiology.

Artificial intelligence (AI) refers to the performance of tasks by machines ordinarily associated with human intelligence. Machine learning (ML) is a ...

AI-based diagnosis of COVID-19 patients using X-ray scans with stochastic ensemble of CNNs.

According to the World Health Organization (WHO), novel coronavirus (COVID-19) is an infectious disease and has a significant social and economic impa...

Detection and analysis of COVID-19 in medical images using deep learning techniques.

The main purpose of this work is to investigate and compare several deep learning enhanced techniques applied to X-ray and CT-scan medical images for ...

Spatialising urban health vulnerability: An analysisof NYC's critical infrastructure during COVID-19.

This paper examines how fragmentation of critical infrastructure impacts the spread of the coronavirus outbreak in New York City at the neighbourhood ...

PASS: Protein Annotation Surveillance Site for Protein Annotation Using Homologous Clusters, NLP, and Sequence Similarity Networks.

Advances in genome sequencing have accelerated the growth of sequenced genomes but at a cost in the quality of genome annotation. At the same time, co...

The Role of Machine Learning and Artificial Intelligence for making a Digital Classroom and its sustainable Impact on Education during Covid-19.

During the Disease outbreak and in the future, there will be a lot of learning. Since the pandemic has interrupted global schooling, remote learning h...

An Agent-based Decision Support for a Vaccination Campaign.

We explore the Covid-19 diffusion with an agent-based model of an Italian region with a population on a scale of 1:1000. We also simulate different va...

Detection of COVID-19 in Chest X-ray Images: A Big Data Enabled Deep Learning Approach.

Coronavirus disease (COVID-19) spreads from one person to another rapidly. A recently discovered coronavirus causes it. COVID-19 has proven to be chal...

Predicting Grocery Store Visits During the Early Outbreak of COVID-19 with Machine Learning.

While non-essential travel was canceled during the coronavirus infectious disease (COVID-19) pandemic, grocery shopping was essential. The objectives ...

Efficient and targeted COVID-19 border testing via reinforcement learning.

Throughout the coronavirus disease 2019 (COVID-19) pandemic, countries have relied on a variety of ad hoc border control protocols to allow for non-es...

Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment.

HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting geneticall...

Postresection Period-Specific Hazard of Recurrence as a Framework for Surveillance Strategy in Patients with Hepatocellular Carcinoma: A Multicenter Outcome Study.

INTRODUCTION: In spite of the high frequency of recurrence of hepatocellular carcinoma (HCC) after resection, little evidence exists to directly help ...

Ten public health strategies to control the Covid-19 pandemic: the Saudi Experience.

Saudi Arabia plays an important strategic role within the Middle East and afar because of its geographical location, and being the host of one of the ...

Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.

This paper presents an overview of some key results from a body of optimization studies that are specifically related to COVID-19, as reported in the ...

FluNet: An AI-Enabled Influenza-Like Warning System.

Influenza is an acute viral respiratory disease that is currently causing severe financial and resource strains worldwide. With the COVID-19 pandemic ...