The project’s objective is to create health information technology (HIT) using information in electronic health records (EHR) to support non-expert clinicians in identifying children at high risk for ASD. The HIT will integrate two components that provide complementary information. The first component will leverage machine learning algorithms to label EHR of children at high risk for autism. Both traditional and deep learning, potentially leveraging each other, will be evaluated while systematically tracking quality and quantity of information in EHR and their effect on performance. The second component will focus on the EHR free text and identify phenotypic behavioral expressions of diagnostic criteria as defined in the Diagnostic and Statistical Manual of Mental Disorders (DSM). Rule-based natural language processing will be combined with machine learning algorithms. Read More
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