Portable Phenotyping System: A Portable Machine-Learning Approach to i2b2 Obesity Challenge

Himanshu Sharma, Chengsheng Mao, Yizhen Zhang, Haleh Vatani, Liang Yao, Yizhen Zhong, Luke Rasmussen, Guoqian D Jiang, Jyotishman Pathak, Yuan Luo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a portable phenotyping system that is capable of integrating both rule-based and statistical machine learning based approaches. Our system utilizes UMLS to extract clinically relevant features from the unstructured text and then facilitates portability across different institutions and data systems by incorporating ODHSI's OMOP Common Data Model (CDM) to standardize necessary data elements. Our system can also store the key components of rule-based systems (e.g., regular expression matches) in the format of OMOP CDM, thus enabling the reuse, adaptation and extension of many existing rule-based clinical NLP systems. We experimented our system on the corpus from i2b2's Obesity Challenge as a pilot study. Our system facilitates portable phenotyping of obesity and its 15 comorbidities based on the unstructured patient discharge summaries, while achieving a performance that often ranked among the top 10 of the challenge participants. This standardization enables a consistent application of numerous rule-based and machine learning based classification techniques downstream.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages86-87
Number of pages2
ISBN (Electronic)9781538667774
DOIs
StatePublished - Jul 16 2018
Externally publishedYes
Event6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 - New York, United States
Duration: Jun 4 2018Jun 7 2018

Other

Other6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018
CountryUnited States
CityNew York
Period6/4/186/7/18

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Keywords

  • i2b2
  • Machine Learning
  • NLP
  • Obesity
  • OMOP CDM
  • Portability

ASJC Scopus subject areas

  • Information Systems and Management
  • Health Informatics

Cite this

Sharma, H., Mao, C., Zhang, Y., Vatani, H., Yao, L., Zhong, Y., Rasmussen, L., Jiang, G. D., Pathak, J., & Luo, Y. (2018). Portable Phenotyping System: A Portable Machine-Learning Approach to i2b2 Obesity Challenge. In Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 (pp. 86-87). [8411818] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICHI-W.2018.00032