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Leveraging Artificial Intelligence and Machine Learning to Advance Environmental Health Research and Decisions
Artificial intelligence (AI) is a technological invention that promises to transform everyday life and the world.
Machine learning algorithms can analyze large volumes of complex data to find patterns and make predictions, often exceeding the accuracy and efficiency of people who are attempting the same task.
Powered by a tremendous growth in data collection and availability as well as computing power and accessibility, AI and machine learning applications are becoming commonplace in many aspects of modern society, as well as in a growing number of scientific disciplines.
Artificial Intelligence Can Now Gauge Your Risk of Cardiovascular Death
Finally, some non-scary artificial intelligence (AI) news that won’t scare the living bejeezus out of you: artificial intelligence has proven to be a key feather in the transformative cap of health care We are benefitted by AI when it can trumpet the need for preventative interventions by predicting such health threats as catching type 1 diabetes and helping predict breast cancer, along with its role in automated operations and precision surgery.
The system, RiskCardio, focuses on patients who have survived an acute coronary syndrome (ACS) and can better predict the risk of death caused by cardiovascular issues that block or reduce blood flow.
The advantage AI offers over traditional analytics and clinical decision-making techniques is unprecedented insight for physicians to gain regarding diagnostics, care processes, treatment variability and outcomes for patients.
Artificial intelligence can now predict El Niño 18 months in advance
Yoo-Geun Ham at Chonnam National University in South Korea and his colleagues built an AI that can predict the development of an El Niño system up to 18 months before it occurs.
They trained the system using historical global oceanic temperature data from 1871 to 1973, as well as nearly 3000 simulations of El Niño events between 1961 and 2005 that had been generated by existing forecasting models.
Artificial intelligence could predict El Niño up to 18 months in advance
As warm waters in the tropical Pacific Ocean shift eastward and trade winds weaken, the weather pattern ripples through the atmosphere, causing drought in southern Africa, wildfires in South America, and flooding on North America’s Pacific coast.
Climate scientists have struggled to predict El Niño events more than 1 year in advance, but artificial intelligence (AI) can now extend forecasts to 18 months, according to a new study.
The work could help people in threatened regions better prepare for droughts and floods, for example by choosing which crops to plant, says William Hsieh, a retired climate scientist in Victoria, Canada, who worked on early El Niño forecasts but who was not involved in the current study.
In this case, researchers trained the neural network on global images of historic sea surface temperatures and deep ocean temperatures to learn how they corresponded to the future emergence of El Niño events.
To get around the shortage of historic El Niño data, the scientists fed the program re-creations of historic ocean conditions produced by a set of reputable climate models, ones frequently used for study climate change, says the study’s lead author, Yoo-Geun Ham, a climate scientist at Chonnam National University in Gwangju, South Korea.
As a result, the scientists could show the computer system not just one set of actual historic data, spanning 1871 to 1973, but several thousand simulations of that same data by the climate models.
- On 15. april 2021
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