ArticleArtificial intelligence in medicine2023
Enriching representation learning using 53 million patient notes through human phenotype ontology embedding.
Article in Artificial intelligence in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Ontology accelerates few-shot learning capability of large language model: A study in extraction of drug efficacy in a rare pediatric epilepsy.International journal of medical informatics · 2025Article
- An effective encoding of human medical conditions in disease space provides a versatile framework for deciphering disease associations.Quantitative biology (Beijing, China) · 2025Article
- Uncovering the Understanding of the Concept of Patient Similarity in Cancer Research and Treatment: Scoping Review.Journal of medical Internet research · 2025Article
- Using Natural Language Processing to Identify Symptomatic Adverse Events in Pediatric Oncology: Tutorial for Clinician Researchers.JMIR bioinformatics and biotechnology · 2025Article
- Deciphering the Natural History ofNeurology · 2025Article
- The clinical and genetic spectrum of paediatric speech and language disorders.Brain : a journal of neurology · 2025Article
- A Longitudinal Exploration ofNeurology. Genetics · 2025Review
- A machine learning decision support tool optimizes WGS utilization in a neonatal intensive care unit.NPJ digital medicine · 2025Article
- Clinical signatures of genetic epilepsies precede diagnosis in electronic medical records of 32,000 individuals.Genetics in medicine : official journal of the American College of Medical Genetics · 2024Article
- Clinical Research Informatics: Contributions from 2023.Yearbook of medical informatics · 2024Review
- A Machine Learning Decision Support Tool Optimizes Whole Genome Sequencing Utilization in a Neonatal Intensive Care Unit.medRxiv : the preprint server for health sciences · 2024Article
- A corpus of GA4GH Phenopackets: case-level phenotyping for genomic diagnostics and discovery.medRxiv : the preprint server for health sciences · 2024Article
- The clinical and genetic spectrum of paediatric speech and language disorders in 52,143 individuals.medRxiv : the preprint server for health sciences · 2024Article
- EAPR: explainable and augmented patient representation learning for disease prediction.Health information science and systems · 2023Article
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9 authors.
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Abstract
The Human Phenotype Ontology (HPO) is a dictionary of >15,000 clinical phenotypic terms with defined semantic relationships, developed to standardize phenotypic analysis. Over the last decade, the HPO has been used to accelerate the implementation of precision medicine into clinical practice. In addition, recent research in representation learning, specifically in graph embedding, has led to notable progress in automated prediction via learned features. Here, we present a novel approach to phenotype representation by incorporating phenotypic frequencies based on 53 million full-text health care notes from >1.5 million individuals. We demonstrate the efficacy of our proposed phenotype embedding technique by comparing our work to existing phenotypic similarity-measuring methods. Using phenotype frequencies in our embedding technique, we are able to identify phenotypic similarities that surpass current computational models. Furthermore, our embedding technique exhibits a high degree of agreement with domain experts' judgment. By transforming complex and multidimensional phenotypes from the HPO format into vectors, our proposed method enables efficient representation of these phenotypes for downstream tasks that require deep phenotyping. This is demonstrated in a patient similarity analysis and can further be applied to disease trajectory and risk prediction.
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