Science 2.0 Approach To Monitoring Kidney Transplant Patients
Sunday, June 29, 2014 - 06:50
in Health & Medicine
A new data analysis technique in the journal PLoS Computational Biology improves monitoring of kidney patients and could lead to changes in the way we understand our health. The research uses the Science 2.0 approach to make sense out of the huge number of clues about a kidney transplant patient's prognosis contained in their blood. Using big data analysis of the samples, scientists were able to crunch hundreds of thousands of variables into a single parameter indicating how a kidney transplant was faring. That allowed the team of physicists, chemists and clinicians to predict poor function of a kidney after only two days in cases that may not previously have been detected as failing until weeks after transplant. read more