Public Health

Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning.

Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 is still a massive challenge due to the spatial complexity of 3D volumes, the labeling difficulty of infection areas, and the slight discrepancy between COVID-19 and other viral pneumonia in chest CT. While a few pioneering works ...

Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia.

The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 2020. Detecting COVID-19 at early stage is essential to deliver proper healthcare to the patients and also to protect the uninfected population. To this end, we develop a dual-sampling attention network to automatically di...

A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT.

Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-b...

Role of 5G-powered remote robotic ultrasound during the COVID-19 outbreak: insights from two cases.

The 2019 Novel Coronavirus disease (COVID-19) broke out in Wuhan, China in December 2019 and spread throughout the world. Early screening and early di...

[Machine learning-based method for interpreting the guidelines of the diagnosis and treatment of COVID-19].

The outbreak of pneumonia caused by novel coronavirus (COVID-19) at the end of 2019 was a major public health emergency in human history. In a short p...

Artificial intelligence and the future of global health.

Concurrent advances in information technology infrastructure and mobile computing power in many low and middle-income countries (LMICs) have raised ho...

Deep Learning Localization of Pneumonia: 2019 Coronavirus (COVID-19) Outbreak.

AI Surveillance during Pandemics: Ethical Implementation Imperatives.

Artificial intelligence surveillance can be used to diagnose individual cases, track the spread of Covid-19, and help provide care. The use of AI for ...

A Bayesian classification model for discriminating common infectious diseases in Zhejiang province, China.

To develop a classification model for accurately discriminating common infectious diseases in Zhejiang province, China.Symptoms and signs, abnormal la...

Time series computational prediction of vaccines for influenza A H3N2 with recurrent neural networks.

Influenza viruses are persistently threatening public health, causing annual epidemics and sporadic pandemics due to rapid viral evolution. Vaccines a...

The most cited and co-cited COVID-19 articles: Knowledge base for rehabilitation team members.

BACKGROUND: The COVID-19 outbreak pandemic is a situation without a tested action plan. Rehabilitation team members have been called for duty with new...

What is Machine Learning? A Primer for the Epidemiologist.

Machine learning is a branch of computer science that has the potential to transform epidemiologic sciences. Amid a growing focus on "Big Data," it of...

Natural Language Processing for the Identification of Surgical Site Infections in Orthopaedics.

BACKGROUND: The identification of surgical site infections for infection surveillance in hospitals depends on the manual abstraction of medical record...

A virus precipitation method for concentration & detection of avian influenza viruses from environmental water resources & its possible application in outbreak investigations.

BACKGROUND & OBJECTIVES: Avian influenza (AI) viruses have been a major cause of public health concern. Wild migratory birds and contaminated environm...

Learning epidemic threshold in complex networks by Convolutional Neural Network.

Deep learning has taken part in the competition since not long ago to learn and identify phase transitions in physical systems such as many-body quant...

IDOMEN: An Extension of Infectious Disease Ontology for MENingitis.

In sub-Saharan African countries the prevention and control of epidemic diseases requires the improvement of the surveillance system for these disease...

A New Approach to Compare the Performance of Two Classification Methods of Causes of Death for Timely Surveillance in France.

Timely mortality surveillance in France is based on the monitoring of electronic death certificates to provide information to health authorities. This...

Artificial neural network-assisted Fourier transform infrared spectroscopy for differentiation of Salmonella serogroups and its application on epidemiological tracing of Salmonella Bovismorbificans outbreak isolates from fresh sprouts.

Salmonellae represent one of the most common bacterial infection reagents in both humans and animals. For detection and epidemiological elucidation of...

Context matters: using reinforcement learning to develop human-readable, state-dependent outbreak response policies.

The number of all possible epidemics of a given infectious disease that could occur on a given landscape is large for systems of real-world complexity...

Artificial intelligence estimates the impact of human papillomavirus types in influencing the risk of cervical dysplasia recurrence: progress toward a more personalized approach.

The objective of this study was to determine whether the pretreatment human papillomavirus (HPV) genotype might predict the risk of cervical dysplasia...