"Machine learning may be able to read everything and find obscure patterns or rare conditions humans would miss, but it also can lack valuable human experience," Rouda said.
By blending the two, Spare5 could tap into the best of both approaches.
"Improving accuracy and completeness of data going into machine learning will improve the model, and it will continue to learn the right associations," Rouda said.
Founded in 2014, Spare5 took in $10 million in Series A funding last August.
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