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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 2 of 2 Research Studies DisplayedGu Y, Leroy G, Pettygrove S
Optimizing corpus creation for training word embedding in low resource domains: a case study in Autism Spectrum Disorder (ASD).
Automating the extraction of behavioral criteria indicative of Autism Spectrum Disorder (ASD) in electronic health records (EHRs) can contribute significantly to the effort to monitor the condition. Word embedding algorithms such as Word2Vec can encode semantic meanings of words in vectors and assist in automated vocabulary discovery from EHRs. However, text available for training word embeddings for ASD is miniscule compared to the billions of tokens typically used. In this study, the investigators evaluated the importance of corpus specificity versus size and hypothesized that for specific domains small corpora can generate excellent word embeddings.
AHRQ-funded; HS024988.
Citation: Gu Y, Leroy G, Pettygrove S .
Optimizing corpus creation for training word embedding in low resource domains: a case study in Autism Spectrum Disorder (ASD).
AMIA Annu Symp Proc 2018 Dec 5;2018:508-17..
Keywords: Autism, Electronic Health Records (EHRs), Health Information Technology (HIT)
Bush RA, Connelly CD, Perez A
Extracting autism spectrum disorder data from the electronic health record.
This study uses electronic health record (EHR) data to examine medical utilization and track outcomes among children with Autism Spectrum Disorder (ASD). The study also identifies challenges inherent in designing inclusive algorithms for identifying individuals with ASD and demonstrates the utility of employing multiple extractions to improve the completeness and quality of EHR data when conducting research.
AHRQ-funded; HS022404.
Citation: Bush RA, Connelly CD, Perez A .
Extracting autism spectrum disorder data from the electronic health record.
Appl Clin Inform 2017 Jul 19;8(3):731-41. doi: 10.4338/aci-2017-02-ra-0029..
Keywords: Autism, Children/Adolescents, Data, Health Information Technology (HIT), Electronic Health Records (EHRs)