Verily creates machine learning tool to aid diagnostic development

Verily has published details of a machine learning approach that may support development of new diagnostic tools. The approach, DeepMass, is designed to improve characterization of disease-relevant protein profiles by tackling a limitation on the use of mass spectrometry. In early tests, DeepMass was more accurate than an existing prediction model and expanded the coverage of known biomarkers when applied to clinical data. Verily, the Alphabet unit formerly known as Google Life Sciences, measures protein profiles to find new disease biomarkers in a range of its programs, including The Project Baseline Health Study that has attracted the support of Pfizer and other drugmakers. These searches for biomarkers use a form of protein mass spectrometry designed to increase the accuracy of protein identification and quantification.