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WASHINGTON Machine learning, a form of artificial intelligence, can predict which women are at high risk of developing gestational diabetes and lead to earlier intervention, according to a new study published in the Endocrine Society s
Journal of Clinical Endocrinology & Metabolism.
Gestational diabetes is a common complication during pregnancy that affects up to 15 percent of pregnant women. High blood sugar in the mother can be dangerous for the baby and lead to complications like stillbirth and premature delivery. Most women are diagnosed with gestational diabetes during the second trimester, but some women are at high risk and could benefit from earlier intervention.
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Credit: DOI number: 10.1038/s41467-020-19863-x
A joint research team co-led by
City University of Hong Kong (CityU) has developed a novel computational tool that can reconstruct and visualise three-dimensional (3D) shapes and temporal changes of cells, speeding up the analysing process from hundreds of hours by hand to a few hours by the computer. Revolutionising the way biologists analyse image data, this tool can advance further studies in developmental and cell biology, such as the growth of cancer cells.
The interdisciplinary study was co-led by
Professor Yan Hong, Chair Professor of Computer Engineering and Wong Chung Hong Professor of Data Engineering in the Department of Electrical Engineering (EE) at CityU, together with biologists from Hong Kong Baptist University (HKBU) and Peking University. Their findings have been published in the scientific journal
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LA JOLLA, CA Most living things need oxygen to grow and thrive. Even cancerous tumors. That s why tumors will readily sprout new blood vessels if their oxygen is starved, creating new lifelines for survival.
A study published today from Scripps Research pinpoints the precise molecular machinery that makes this happen, providing scientific insights that can potentially be translated into medicines that help kill tumors and stop cancer from spreading in the body.
The findings also may enable new interventions that promote healthy blood-vessel development for people with heart disease and other conditions, says the study s leader Xiang-Lei Yang, PhD, a professor In the Department of Molecular Medicine at Scripps Research.
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Math Daily News
2020 DEC 18 (NewsRx) By a News Reporter-Staff News Editor at Math Daily News A new study on Engineering is now available. According to news reporting originating from Xinyu, People’s Republic of China, by NewsRx correspondents, research stated, “Residential power scheduling for demand response in a smart grid is a complex task. The traditional methods aim to minimize consumption costs and maximize consumption payoffs.”
Financial support for this research came from National Natural Science Foundation of China.
Our news editors obtained a quote from the research from Xinyu University, “In this paper, a power scheduling algorithm based on cost efficiency for smart homes is proposed to improve consumers’ consumption efficiency and satisfaction. In this proposed method, a definition of cost efficiency for residential power scheduling is introduced. Consumers’ consumption costs are modelled based on electricity payments and users’ discomfort.
Artificial Intelligence Predicts Gestational Diabetes by Colleen Fleiss on December 22, 2020 at 11:10 PM
Machine learning helped predict women at high risk of developing gestational diabetes, revealed a new study published in the Endocrine Society s Journal of Clinical Endocrinology & Metabolism. Machine learning is a form of artificial intelligence.
Gestational diabetes is a common complication during pregnancy that affects up to 15 percent of pregnant women. High blood sugar in the mother can be dangerous for the baby and lead to complications like stillbirth and premature delivery. Most women are diagnosed with gestational diabetes during the second trimester, but some women are at high risk and could benefit from earlier intervention.