Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.

The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO\u27s interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes

Session 11: \u3cem\u3eDevelopment and Evaluation of a Rural SARS-Cov-2 Hospital Admissions Predictive Model\u3c/em\u3e

Ongoing evolution of the SARS-Cov-2 virus has propelled the world into a state of the unknown. The impact upon healthcare has been immense. Case numbers and hospitalizations have grown at rapid rates as new variants exhibit higher transmissibility. Efforts to gain foresight into the evolving conditions have been underway for organizational and planning purposes alike. Recognizing that there are repercussions from both, underestimates and overestimates of predicted hospitalizations, we have developed a model that leverages sophisticated data science techniques which employ foundational epidemiologic methods. This has allowed us to account for this highly volatile and dynamic landscape and forecast hospital admissions with reasonable accuracy throughout the course of this pandemic

Deep phenotyping for patients by patients: a lay-friendly version of the Human Phenotype Ontology

<div>The Human Phenotype Ontology (HPO) has become the de facto standard representation of clinical “deep phenotype” data for computational comparison of abnormalities and for use in genetic disease diagnostics. The HPO enables non-exact matching of sets of phenotypic features (phenotype profile) against known diseases, other patients, and model organisms. The algorithms have been implemented into many variant prioritization tools and are used by the 100,000 Genomes project, the NIH Undiagnosed Diseases Program/Network, and thousands of other clinics, labs, tools, and databases. </div><div><br></div><div>Patients themselves are an eager and untapped source of accurate information about symptoms and phenotypes - some of which may go unnoticed by the clinician. However, medical terminology is often perplexing to patients, making it difficult to use resources like the HPO. Here, we systematically added layperson synonyms with approximately 60% being translatable into layperson terminology. Analyses suggest that the lay-HPO has the features required to be useful in a diagnostic setting, in that lay terms are: a) sufficiently specific and, b) well-represented in our disease-to-phenotype database that is utilized by the aforementioned tools for differential diagnostics. A new patient-centered tool aims to help patients assist clinicians in creating robust computational phenotype profiles to improve molecular diagnostic rates and be active participants in their diagnostic odysseys. </div

Plain-language medical vocabulary for precision diagnosis.

Nat Genet 2018 Apr; 50(4):474-476

Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.

The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO's interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes

Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources

The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO's interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes

Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources

The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO's interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes.National Institutes of Health (NIH), Monarch Initiative [OD #5R24OD011883]; Forums for Integrative Phenomics [U13 CA221044-01]; NCATS Data Translator [1OT3TR002019]; NCATS National Center for Digital Health Informatics Innovation [U24 TR002306]; NIH Data Commons [1 OT3 OD02464-01 UNCCH]; Cost Action CA 16118 Neuro-MIG; British Heart Foundation Programme Grant [RG/13/5/30112]; Division of Intramural Research; NIAID; NIH; E-RARE project Hipbi-RD [01GM1608]; European Union’s Horizon 2020 Research and Innovation Programme [779257]. Funding for open access charge: NIH; Donald A. Roux Family Fund (to P.N.R.)