Researchers at Geisinger have found that a computer algorithm developed using echocardiogram videos of the heart can predict mortality within a year.
The algorithm an example of what is known as machine learning, or artificial intelligence (AI) outperformed other clinically used predictors, including pooled cohort equations and the Seattle Heart Failure score.
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As a new presidential administration takes steps to examine options to control the spread of COVID-19 through increased testing, epidemiologists at The University of Texas at Austin and other institutions have a new analysis that shows the value of having all people in the U.S. tested on a regular, rotating basis to slow the spread of the novel coronavirus and the loss of life from COVID-19. The team s model is outlined in a paper published online today in
The Lancet Public Health.
With the introduction of accurate and inexpensive rapid tests, researchers say there is an optimal testing schedule that minimizes costs as well as the loss of life and economic damage from hospitalizations and quarantine in different regions, based on the rate at which the virus is spreading.
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USC researchers have developed a new method to counter emergent mutations of the coronavirus and hasten vaccine development to stop the pathogen responsible for killing thousands of people and ruining the economy.
Using artificial intelligence (AI), the research team at the USC Viterbi School of Engineering developed a method to speed the analysis of vaccines and zero in on the best potential preventive medical therapy.
The method is easily adaptable to analyze potential mutations of the virus, ensuring the best possible vaccines are quickly identified solutions that give humans a big advantage over the evolving contagion. Their machine-learning model can accomplish vaccine design cycles that once took months or years in a matter of seconds and minutes, the study says.
A warmer global climate can cause mutations to have more severe consequences for the health of organisms through their detrimental effect on protein function. This may have major repercussions on organisms ability to adapt to, and survive in, the altered habitats of the future. This is shown in a new Uppsala University research study now published in the scientific journal
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Temperature rise due to climate change has negatively affected labour productivity in the past decades and will keep damaging it, potentially at a higher extent than what has been estimated in the literature up to now. In South Africa, a future scenario with severe climate change will feature a reduction of per capita GDP of up to 20% by the end of the century, compared to an idealized future without the impacts of a changing climate.
This is what emerges from the study Climate change and development in South Africa: the impact of rising temperatures on economic productivity and labour availability , coordinated by the CMCC Foundation and RFF-CMCC European Institute on Economics and the Environment (EIEE) and conducted in collaboration with the Athens University of Economics and Business, recently published in the Journal