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Computer scientists developed method for identifying disease biomarkers with high accuracy


Researchers are developing a deep learning network capable of detecting disease biomarkers with a much higher degree of accuracy.
Experts at the University of Waterloo’s Cheriton School of Computer Science have created a deep neural network that achieves 98 per cent detection of peptide features in a dataset. That means scientists and medical practitioners have a greater chance of discovering possible diseases through tissue sample analysis.
There are multiple existing techniques for detecting diseases by analyzing the protein structure of bio-samples. Computer programs increasingly play a part in this process by examining the large amount of data produced in such tests to pinpoint specific markers of disease.
“But exi …

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