October 31, 2013 by Suzanne Elvidge in Data mining

Mining electronic medical records for better healthcare

A computer scientist from the University of Texas at Arlington is developing a way to mine patients’ electronic medical record (EMR) data. Being able to exploit this wealth of data, which is already available but is very difficult to access, could make a significant difference in personalising medicine for patients.

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October 25, 2013 by Suzanne Elvidge in Data mining, Drug development

Mining mouse movements for psychiatric drug R&D

Developing drugs for different psychiatric diseases is difficult, partly because the animal models aren’t always effective. Data mining could be coming to the rescue though, according to researchers at Tel Aviv University‘s Department of Zoology, working in collaboration with the University of Maryland. The key to successful drug development is

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October 18, 2013 by Suzanne Elvidge in Data mining, Drug development

Data mining to cut side effects

Researchers at Berg Health and the Icahn School of Medicine at Mount Sinai are working together, using data mining and data analytics, mathematical models, biological networks analysis, and animal models to find better and safer therapeutics. This is known as systems pharmacology, and allows researchers to look at how drugs

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October 07, 2013 by Suzanne Elvidge in Data mining, Healthcare big data analysis

Data driven machine learning spots stroke risk

A team of US medics, data scientists and engineers have collaborated to create a data-driven machine learning model that could find those stroke patients who are most likely to be at risk of a serious adverse event following a ruptured brain aneurysm. Data mining and machine learning has applications across

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