Research

Brazilian Scientists Develop COVID-19 Accelerometer

Researchers at São Paulo State University (UNESP) in Araçatuba, Brazil, have developed a computational tool that acts like a "COVID-19 accelerometer," plotting in real time the rate at which growth is accelerating or decelerating in more than 200 countries and territories.

App Determines COVID-19 Disease Severity Using Artificial Intelligence, Biomarkers

A new mobile app can help clinicians determine which patients with the novel coronavirus (COVID-19) are likely to have severe cases. Created by researchers at NYU College of Dentistry, the app uses artificial intelligence (AI) to assess risk factors and key biomarkers from blood tests, producing a COVID-19 "severity score."

Computer Modelling Predicts where Vaccines Are Needed Most

Researchers have developed a model that can estimate regional disease burden and the impact of vaccination, even in the absence of robust surveillance data, a study in eLife reveals.

The report, originally published on May 26, highlights areas that would have the greatest benefit from initiating a vaccination programme against the virus, Japanese encephalitis (JE).

Bluetooth Technology, the Best Ally to Detect COVID-19 Cases through Smartphone Contact Tracing

"Tracers have been and are essential to manage the pandemic. Today, the tracing is done by hand and this work is slow and inaccurate. However, as we have seen, technology can be highly useful: contact tracing with smartphones and smartclocks help find out who has been in contact with an infected person, thanks to the use of

Artificial Intelligence can Improve How Chest Images Are Used in Care of COVID-19 Patients

According to a recent report by Johns Hopkins Medicine researchers, artificial intelligence (AI) should be used to expand the role of chest X-ray imaging - using computed tomography, or CT - in diagnosing and assessing coronavirus infection so that it can be more than just a means of screening for signs of COVID-19 in a patient's lungs.

Researchers Identify Healthcare Data Defects

Researchers at the University of Maryland, Baltimore County (UMBC) have developed a method to investigate the quality of healthcare data using a systematic approach, which is based on creating a taxonomy for data defects thorough literature review and examination of data. Using that taxonomy, the researchers developed software that automatically detects data defects effectively and efficiently.

Digital Contact Tracing for COVID-19: An Analysis of Strengths and Limitations

An article in CMAJ (Canadian Medical Association Journal) analyzes the strengths and limitations of digital contact tracing for people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to help governments decide if and how they might adopt this technology.