Success Story: Improving DNA Mixture Interpretation with the Help of Machine Learning

NIJ and Syracuse University

Report Date

March 2019

Impact

“This is something that every DNA crime lab worldwide should investigate. We now have a tool that with the press of one button does the entire suite of services and provides you with the end result. Having the simple decisions made for you enables focus on addressing the issues of most importance.” —Vic Meles, Marketing & Business Director, NicheVision

Click here to read the full report

Links

• NicheVision

• PACE: Probabilistic Assessment for Contributor Estimation— A machine learning-based assessment of the number of contributors in DNA mixtures. Forensic Science International: Genetics, 2018.

• A hybrid approach to increase the informedness of CE-based data using locus-specific thresholding and machine learning, Forensic Science International: Genetics, 2018.