Method to identify undetected drug suicides wins top NIDA Addiction Science Award

A project that identified and tested a bioinformatics program that can help identify underreported suicides linked to drug overdoses was awarded the first-place distinction at the 2018 Intel International Science and Engineering Fair (ISEF)—the world’s largest science competition for high school students. The awards are coordinated by the National Institute on Drug Abuse (NIDA), part of the National Institutes of Health, and Friends of NIDA, a coalition that supports NIDA’s mission. The Intel ISEF Addiction Science Awards were presented at a ceremony Thursday night at the David L. Lawrence Convention Center in Pittsburgh.

The first place award went to 17-year old Mia Yu and 14-year old Daphne Liu from West High School in Salt Lake City for their project “Undetected Suicide: Classification of Undetermined Drug-Related Deaths Using Machine Learning Techniques.” The two students compared three machine learning models to determine how well they could identify undetermined overdose deaths as actual suicides. Using existing machine platforms, they first plugged in overdose deaths already classified as either suicide or accidental. From there, they identified the most accurate computational model. They then used that model to measure the overdose deaths listed as undetermined. Using data from the state of Utah, the machine learning technique determined that drug-related suicide deaths were underreported by 34 percent.

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Will Savage

Quantum Units Continuing Education provides online CEU training's to licensed professional mental health therapists, counselors, social workers and nurses. Our blog provides updates in the field of news and research related to mental health and substance abuse treatment.