@conference {ICBO_2018_69,
	title = {ICBO_2018_69: An (ontological) patient perspectiv},
	booktitle = {International Conference on Biomedical Ontology (ICBO 2018)},
	series = {Proceedings of the International Conference on Biological Ontology (2018)},
	year = {2018},
	month = {08/06/2018},
	publisher = {International Conference on Biological Ontology},
	organization = {International Conference on Biological Ontology},
	abstract = {The Human Phenotype Ontology (HPO) has become the de facto standard representation of clinical {\textquotedblleft}deep phenotype{\textquotedblright} data for computational comparison of abnormalities and for use in genetic disease diagnostics. Using semantic similarity methods, the HPO is used to match non-exact sets of phenotypic features against known diseases, other patients, and model organisms. Algorithms based on HPO have been implemented into variant prioritization tools and are used by the 100,000 Genomes project, the NIH Undiagnosed Diseases Program/Network, and many other clinics, labs, tools, and databases. However, patient phenotypes can be laborious to capture adequately, and some phenotypes go unnoticed by the clinician (such as those only seen at home). Patients themselves are an eager and untapped source of information about symptoms and phenotypes, however, medical terminology is often perplexing to them, making it difficult to use resources like the HPO. Therefore, to support use of the HPO by patients directly, we have created a {\textquoteleft}layperson{\textquoteright} translation. Approximately 36\% of the HPO terms have at least one layperson synonym, 89\% of the diseases annotated to HPO have at least one HPO annotation with a layperson synonym, and 60\% of all disease annotations refer to HPO terms with lay translations. This coverage suggests that the layperson HPO would be useful in a diagnostic setting despite incomplete coverage. To evaluate the diagnostic utility of this lay translation, we created synthetic profiles ({\textquotedblleft}slim annotations{\textquotedblright}) for each annotated disease in the MONDO disease ontology and compared these slim annotations against the gold standard curated set. We also permuted these profiles by adding or removing annotations to determine how robust the lay annotation profiles might be in the face of missing or noisy data coming from patients. In order to evaluate the lay person profiles, we measured the semantic similarity between HPO gold standard annotations and the derived profiles (with and without noise added). 57\% of profiles scored 80\% similarity or higher, and 75\% of profiles scored 70\% similarity or higher. These results highlight the potential impact that the use of a patient-centered ontology view may have in clinical diagnostics for rare disease patients.},
	keywords = {Medicine, Personalized medicine, phenotype, Translational science},
	url = {http://icbo2018.cgrb.oregonstate.edu/},
	author = {Melissa Haendel and Nicole Vasilevsky and Kayli Rageth and Sebastian Koehler and Peter Robinson and Julie McMurry and Kent Shefchek and Catherine Brownstein and Ingrid Holm and Chris Mungall}
}
