ArticleJournal of neurodevelopmental disorders2022
Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records.
Article in Journal of neurodevelopmental disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 18 citations in OpenAlex.
- Efficacy and Safety of AltibrainCurrent pharmaceutical design · 2025Trial
- Health databases and early identification of autism spectrum disorder: a scoping review.BMJ open · 2026Article
- Natural Language Processing Applied to Psychiatric Clinical Notes: Scoping Review.JMIR medical informatics · 2026Article
- Using clinical notes to identify children with speech-language delay and understand differences in diagnostic timing.JAMIA open · 2026Article
- Multimodal AI for risk stratification in autism spectrum disorder: integrating voice and screening tools.NPJ digital medicine · 2025Article
- Speech pattern disorders in verbally fluent individuals with autism spectrum disorder: a machine learning analysis.Frontiers in neuroinformatics · 2025Article
- Implications of mappings between International Classification of Diseases clinical diagnosis codes and Human Phenotype Ontology terms.JAMIA open · 2024Article
- Semantics-enabled biomedical literature analytics.Journal of biomedical informatics · 2024Article
- Enhancing phenotype recognition in clinical notes using large language models: PhenoBCBERT and PhenoGPT.Patterns (New York, N.Y.) · 2024Article
- Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT.ArXiv · 2023Article
- Genomic architecture of autism spectrum disorder in Qatar: The BARAKA-Qatar Study.Genome medicine · 2023Article
- Assessment of autonomic symptom scales in patients with neurodevelopmental diagnoses using electronic health record data.Research in autism spectrum disorders · 2023Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundAutism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyping ASD due in part to the lack of a validated, standardized vocabulary to characterize clinical phenotypic presentation of ASD. Although the human phenotype ontology (HPO) plays an important role in delineating nuanced phenotypes for rare genetic diseases, it is inadequate to capture characteristic of behavioral and psychiatric phenotypes for individuals with ASD. There is a clear need, therefore, for a well-established phenotype terminology set that can assist in characterization of ASD phenotypes from patients' clinical narratives.
methodsTo address this challenge, we used natural language processing (NLP) techniques to identify and curate ASD phenotypic terms from high-quality unstructured clinical notes in the electronic health record (EHR) on 8499 individuals with ASD, 8177 individuals with non-ASD psychiatric disorders, and 8482 individuals without a documented psychiatric disorder. We further performed dimensional reduction clustering analysis to subgroup individuals with ASD, using nonnegative matrix factorization method.
resultsThrough a note-processing pipeline that includes several steps of state-of-the-art NLP approaches, we identified 3336 ASD terms linking to 1943 unique medical concepts, which represents among the largest ASD terminology set to date. The extracted ASD terms were further organized in a formal ontology structure similar to the HPO. Clustering analysis showed that these terms could be used in a diagnostic pipeline to differentiate individuals with ASD from individuals with other psychiatric disorders.
conclusionOur ASD phenotype ontology can assist clinicians and researchers in characterizing individuals with ASD, facilitating automated diagnosis, and subtyping individuals with ASD to facilitate personalized therapeutic decision-making.
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