Subgrouping rare disease patients leveraging the human phenotype ontology embeddings

Feichen Shen; Andrew Wen; Hongfang Liu

doi:10.1109/CBMS49503.2020.00039

Subgrouping rare disease patients leveraging the human phenotype ontology embeddings

Feichen Shen, Andrew Wen, Hongfang Liu

Digital Health Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

In the USA, rare diseases are defined as those affecting fewer than 200,000 patients at any given time. It usually takes substantial time and long journey for rare disease patients to seek care before receiving a correct diagnosis. Making the right phenotypic characterization is the initial step to speed up such differential diagnosis at early time and the Human Phenotype Ontology (HPO) is a comprehensive knowledgebase supporting this goal. Previously, we have constructed various node embeddings for the HPO incorporating heterogeneous biomedical knowledge repositories. In this study, we applied unsupervised learning strategies over different HPO embeddings, aiming to further subgroup rare disease patients based on phenotypic characterizations.

Original language	English (US)
Title of host publication	Proceedings - 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020
Editors	Alba Garcia Seco de Herrera, Alejandro Rodriguez Gonzalez, KC Santosh, Zelalem Temesgen, Bridget Kane, Paolo Soda
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	169-172
Number of pages	4
ISBN (Electronic)	9781728194295
DOIs	https://doi.org/10.1109/CBMS49503.2020.00039
State	Published - Jul 2020
Event	33rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2020 - Virtual, Online, United States Duration: Jul 28 2020 → Jul 30 2020

Publication series

Name	Proceedings - IEEE Symposium on Computer-Based Medical Systems
Volume	2020-July
ISSN (Print)	1063-7125

Conference

Conference	33rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2020
Country/Territory	United States
City	Virtual, Online
Period	7/28/20 → 7/30/20

Keywords

Human phenotype ontology embeddings
Patients subgrouping
Phenotypic characterization
Rare disease

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging
Computer Science Applications

Access to Document

10.1109/CBMS49503.2020.00039

Cite this

Shen, F., Wen, A., & Liu, H. (2020). Subgrouping rare disease patients leveraging the human phenotype ontology embeddings. In A. G. S. de Herrera, A. Rodriguez Gonzalez, KC. Santosh, Z. Temesgen, B. Kane, & P. Soda (Eds.), Proceedings - 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020 (pp. 169-172). Article 9183079 (Proceedings - IEEE Symposium on Computer-Based Medical Systems; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CBMS49503.2020.00039

Subgrouping rare disease patients leveraging the human phenotype ontology embeddings. / Shen, Feichen; Wen, Andrew; Liu, Hongfang.
Proceedings - 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020. ed. / Alba Garcia Seco de Herrera; Alejandro Rodriguez Gonzalez; KC Santosh; Zelalem Temesgen; Bridget Kane; Paolo Soda. Institute of Electrical and Electronics Engineers Inc., 2020. p. 169-172 9183079 (Proceedings - IEEE Symposium on Computer-Based Medical Systems; Vol. 2020-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Shen, F, Wen, A & Liu, H 2020, Subgrouping rare disease patients leveraging the human phenotype ontology embeddings. in AGS de Herrera, A Rodriguez Gonzalez, KC Santosh, Z Temesgen, B Kane & P Soda (eds), Proceedings - 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020., 9183079, Proceedings - IEEE Symposium on Computer-Based Medical Systems, vol. 2020-July, Institute of Electrical and Electronics Engineers Inc., pp. 169-172, 33rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2020, Virtual, Online, United States, 7/28/20. https://doi.org/10.1109/CBMS49503.2020.00039

Shen F, Wen A, Liu H. Subgrouping rare disease patients leveraging the human phenotype ontology embeddings. In de Herrera AGS, Rodriguez Gonzalez A, Santosh KC, Temesgen Z, Kane B, Soda P, editors, Proceedings - 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 169-172. 9183079. (Proceedings - IEEE Symposium on Computer-Based Medical Systems). doi: 10.1109/CBMS49503.2020.00039

Shen, Feichen ; Wen, Andrew ; Liu, Hongfang. / Subgrouping rare disease patients leveraging the human phenotype ontology embeddings. Proceedings - 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020. editor / Alba Garcia Seco de Herrera ; Alejandro Rodriguez Gonzalez ; KC Santosh ; Zelalem Temesgen ; Bridget Kane ; Paolo Soda. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 169-172 (Proceedings - IEEE Symposium on Computer-Based Medical Systems).

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Subgrouping rare disease patients leveraging the human phenotype ontology embeddings

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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