Structural Analysis of Biomedical Ontologies Center  

Organization profile

Organization profile

The Structural Analysis of Biomedical Ontologies Center (SABOC) is an interdisciplinary research center linking computer science and medicine. It deals with medical terminologies and ontologies, a subject of study that is a sub-field of Medical Informatics. Many biomedical terminologies are measured in the tens of thousands to hundreds of thousands of terms, including drug names and their chemical ingredients, symptoms, diagnoses, body parts, medical procedures, medical devices, infectious agents and accidents, among others. Understanding these terms and finding inconsistencies with textual representations is difficult, and we therefore use graphical representations: biomedical terminologies appear as networks in which the terms are symbolized as boxes and the relationships between pairs of terms are symbolized as arrows. Without a sophisticated approach, visualizing these networks on a computer screen can lead to failure. The core research efforts of SABOC are to develop small abstraction networks that summarize large biomedical terminologies; to visualize abstraction networks on a computer screen in a manner that is easier to comprehend than the original terminologies; and to perform quality assurance on the original terminologies by using the abstraction networks to find and remove inconsistencies. As biomedical terminologies are increasingly used in applications such as electronic health records, ensuring that terminologies are free of inconsistencies helps ensure the correctness of these applications. SABOC is currently funded by a three-year, $1.75 million grant from the National Institutes of Health.

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  • Mining of EHR for interface terminology concepts for annotating EHRs of COVID patients

    Keloth, V. K., Zhou, S., Lindemann, L., Zheng, L., Elhanan, G., Einstein, A. J., Geller, J. & Perl, Y., Dec 2023, In: BMC Medical Informatics and Decision Making. 23, 40.

    Research output: Contribution to journalArticlepeer-review

    Open Access
  • A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology

    He, Y., Yu, H., Huffman, A., Lin, A. Y., Natale, D. A., Beverley, J., Zheng, L., Perl, Y., Wang, Z., Liu, Y., Ong, E., Wang, Y., Huang, P., Tran, L., Du, J., Shah, Z., Shah, E., Desai, R., Huang, H. H., Tian, Y., & 23 othersMerrell, E., Duncan, W. D., Arabandi, S., Schriml, L. M., Zheng, J., Masci, A. M., Wang, L., Liu, H., Smaili, F. Z., Hoehndorf, R., Pendlington, Z. M., Roncaglia, P., Ye, X., Xie, J., Tang, Y. W., Yang, X., Peng, S., Zhang, L., Chen, L., Hur, J., Omenn, G. S., Athey, B. & Smith, B., Dec 2022, In: Journal of Biomedical Semantics. 13, 1, 25.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    3 Scopus citations
  • CHARACTERIZING MEDICAL ANDROID APPS

    Samuel, R., Neamtiu, I., Rahaman, S. & Geller, J., 2022, 15th International Conference on ICT, Society and Human Beings, ICT 2022, 19th International Conference on Web Based Communities and Social Media, WBC 2022 and 14th International Conference on e-Health, EH 2022 - Held at the 16th Multi Conference on Computer Science and Information Systems, MCCSIS 2022. IADIS Press, p. 155-162 8 p. (15th International Conference on ICT, Society and Human Beings, ICT 2022, 19th International Conference on Web Based Communities and Social Media, WBC 2022 and 14th International Conference on e-Health, EH 2022 - Held at the 16th Multi Conference on Computer Science and Information Systems, MCCSIS 2022).

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