Programmers Develop AI Solutions to Read, Classify Injury Records

NIOSH has announced the winners of an to develop an algorithm that best uses artificial intelligence, or AI, to automatically read injury records and classify them in occupational health and safety surveillance systems. When an employee is injured at work, someone must write explanations of how the injury occurred, read all the narratives, and assign codes to classify injuries. According to NIOSH, this process takes time and is open to human error. First place went to Raymond van Venetië, a doctoral student in Numerical Mathematics at the University of Amsterdam in the Netherlands, whose submission improved NIOSH’s ability to classify worker injuries from the agency’s baseline of 82 percent accuracy to nearly 90 percent accuracy. NIOSH will use van Venetië’s program to build a web tool that OHS professionals can use to classify injury narratives. Competitors from around the world, including Russia, China, India, and the United States, submitted 961 entries. Other top-placing participants include a senior data scientist at Sherbank AI lab in Russia; a developer and data scientist from China; a biostatistician at the School of Medicine at Emory University in Atlanta, Georgia; and a full stack engineer from Bangalore, India. This was the first competition of its kind from NIOSH and its parent organization, CDC. An overview of the competition is available on a website called .