MedTech News

.................... by Andrew Celentano

AI tool debuts with better genomic predictions and explanations

Artificial intelligence has taken the world by storm. In biology, AI tools called deep neural networks (DNNs) have proven invaluable for predicting the results of genomic experiments. Their usefulness has these tools poised to set the stage for efficient, AI-guided research and potentially lifesaving discoveries—if scientists can work out the kinks. The findings are published in the journal npj Artificial Intelligence.

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Machine-learned biomarker identifies those at high risk for liver cancer

Researchers led by Xian-Yang Qin at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score that predicts the risk of liver cancer. Published in the journal Proceedings of the National Academy of Sciences, the study establishes that the protein MYCN drives liver tumorigenesis, specifically of the type of tumors found in the deadliest subtype of liver cancer.

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Stopping fatal blood loss with clay

Traumatic injury is the third leading cause of death in the state of Texas, surpassing strokes, Alzheimer’s disease and diabetes, according to the Centers for Disease Control and Prevention. A massive number of these deaths are the result of uncontrolled bleeding. “Severe blood loss can rapidly lead to hemorrhagic shock,” said Dr. Akhilesh Gaharwar, a biomedical engineering professor at Texas A&M University. “Many patients die within one to two hours of injury. This critical period is often referred to as the ‘golden hour.'”

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