Computer scientists develop 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 percent 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.