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159 results on '"Elhanan, Gai"'

2. Combining rare and common genetic variants improves population risk stratification for breast cancer

Author

Bolze, Alexandre, Kiser, Daniel, Schiabor Barrett, Kelly M., Elhanan, Gai, Schnell Blitstein, Jamie M., Neveux, Iva, Dabe, Shaun, Reed, Harry, Anderson, Alexa, Metcalf, William J., Orlova, Ekaterina, Thibodeau, Ildiko, Telis, Natalie, Jiang, Ruomu, Washington, Nicole L., Ferber, Matthew J., Hajek, Catherine, Cirulli, Elizabeth T., and Grzymski, Joseph J.

Published
2024
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4. FRI-195 Genetically determined circulating protein biomarkers and risk of advanced fibrosis

Author

Wang, Jun, primary, Cuellar-Partida, Gabriel, additional, Read, Robert W., additional, Schlauch, Karen A., additional, Elhanan, Gai, additional, Metcalf, W. James, additional, Boyette, Lisa, additional, Watkins, Timothy R., additional, Grzymski, Joseph J., additional, Patterson, Scott D., additional, Iqbal, Shahed, additional, and Billin, Andrew N., additional

Published
2024
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8. From SNOMED CT to Uberon: Transferability of evaluation methodology between similarly structured ontologies

Author

Elhanan, Gai, Ochs, Christopher, Mejino, Jose LV, Liu, Hao, Mungall, Christopher J, and Perl, Yehoshua

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Biological Ontologies, Semantics, Systematized Nomenclature of Medicine, Anatomy ontology, Disjoint abstraction network, Overlapping concepts, Quality assurance, Semantic complexity, Information and Computing Sciences, Engineering, Medical Informatics, Biomedical and clinical sciences, Health sciences, Information and computing sciences
Abstract

ObjectiveTo examine whether disjoint partial-area taxonomy, a semantically-based evaluation methodology that has been successfully tested in SNOMED CT, will perform with similar effectiveness on Uberon, an anatomical ontology that belongs to a structurally similar family of ontologies as SNOMED CT.MethodA disjoint partial-area taxonomy was generated for Uberon. One hundred randomly selected test concepts that overlap between partial-areas were matched to a same size control sample of non-overlapping concepts. The samples were blindly inspected for non-critical issues and presumptive errors first by a general domain expert whose results were then confirmed or rejected by a highly experienced anatomical ontology domain expert. Reported issues were subsequently reviewed by Uberon's curators.ResultsOverlapping concepts in Uberon's disjoint partial-area taxonomy exhibited a significantly higher rate of all issues. Clear-cut presumptive errors trended similarly but did not reach statistical significance. A sub-analysis of overlapping concepts with three or more relationship types indicated a much higher rate of issues.ConclusionsOverlapping concepts from Uberon's disjoint abstraction network are quite likely (up to 28.9%) to exhibit issues. The results suggest that the methodology can transfer well between same family ontologies. Although Uberon exhibited relatively few overlapping concepts, the methodology can be combined with other semantic indicators to expand the process to other concepts within the ontology that will generate high yields of discovered issues.

Published
2017

10. Pathogenic variants in actionable MODY genes are associated with type 2 diabetes

Author

Bonnefond, Amélie, Boissel, Mathilde, Bolze, Alexandre, Durand, Emmanuelle, Toussaint, Bénédicte, Vaillant, Emmanuel, Gaget, Stefan, Graeve, Franck De, Dechaume, Aurélie, Allegaert, Frédéric, Guilcher, David Le, Yengo, Loïc, Dhennin, Véronique, Borys, Jean-Michel, Lu, James T., Cirulli, Elizabeth T., Elhanan, Gai, Roussel, Ronan, Balkau, Beverley, Marre, Michel, Franc, Sylvia, Charpentier, Guillaume, Vaxillaire, Martine, Canouil, Mickaël, Washington, Nicole L., Grzymski, Joseph J., and Froguel, Philippe

Published
2020
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14. Inhibition of HECT E3 ligases as potential therapy for COVID-19

Author

Novelli, Giuseppe, Liu, Jing, Biancolella, Michela, Alonzi, Tonino, Novelli, Antonio, Patten, J. J., Cocciadiferro, Dario, Agolini, Emanuele, Colona, Vito Luigi, Rizzacasa, Barbara, Giannini, Rosalinda, Bigio, Benedetta, Goletti, Delia, Capobianchi, Maria Rosaria, Grelli, Sandro, Mann, Justin, McKee, Trevor D., Cheng, Ke, Amanat, Fatima, Krammer, Florian, Guarracino, Andrea, Pepe, Gerardo, Tomino, Carlo, Tandjaoui-Lambiotte, Yacine, Uzunhan, Yurdagul, Tubiana, Sarah, Ghosn, Jade, Notarangelo, Luigi D., Su, Helen C., Abel, Laurent, Cobat, Aurélie, Elhanan, Gai, Grzymski, Joseph J., Latini, Andrea, Sidhu, Sachdev S., Jain, Suresh, Davey, Robert A., Casanova, Jean-Laurent, Wei, Wenyi, and Pandolfi, Pier Paolo

Published
2021
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15. Combining rare and common genetic variants improves population risk stratification for breast cancer

Author

Bolze, Alexandre, primary, Kiser, Daniel, additional, Schiabor Barrett, Kelly M, additional, Elhanan, Gai, additional, Schnell Blitstein, Jamie M, additional, Neveux, Iva, additional, Dabe, Shaun, additional, Reed, Harry, additional, Anderson, Alexa, additional, Metcalf, William J, additional, Orlova, Ekaterina, additional, Thibodeau, Ildiko, additional, Telis, Natalie, additional, Jiang, Ruomu, additional, Washington, Nicole L, additional, Ferber, Matthew J, additional, Hajek, Catherine, additional, Cirulli, Elizabeth T, additional, and Grzymski, Joseph J, additional

Published
2023
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45. Summarizing an Ontology: A “Big Knowledge” Coverage Approach.

Author

Ling Zheng, Perl, Yehoshua, Elhanan, Gai, Ochs, Christopher, Geller, James, and Halper, Michael

Abstract

Maintenance and use of a large ontology, consisting of thousands of knowledge assertions, are hampered by its scope and complexity. It is important to provide tools for summarization of ontology content in order to facilitate user “big picture” comprehension. We present a parameterized methodology for the semi-automatic summarization of major topics in an ontology, based on a compact summary of the ontology, called an “aggregate partial-area taxonomy”, followed by manual enhancement. An experiment is presented to test the effectiveness of such summarization measured by coverage of a given list of major topics of the corresponding application domain. SNOMED CT’s Specimen hierarchy is the test-bed. A domain-expert provided a list of topics that serves as a gold standard. The enhanced results show that the aggregate taxonomy covers most of the domain’s main topics. [ABSTRACT FROM AUTHOR]

Published
2017
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46. Auditing SNOMED Integration into the UMLS for Duplicate Concepts

Author

Huang, Kuo-Chuan, Geller, James, Elhanan, Gai, Perl, Yehoshua, and Halper, Michael

Subjects
Humans, Systematized Nomenclature of Medicine, Articles, Unified Medical Language System, Semantics
Abstract

The UMLS contains terms from many sources. Every update of a source requires reintegration. Each new term needs to be assigned to a preexisting UMLS concept, or a new concept must be created. Whenever the integration process unnecessarily creates a new concept, this is undesirable. We report on a method to detect such undesirable duplicate concepts. Terms are removed from the UMLS and reintegrated using "piecewise synonym generation." The concept of the reintegrated term is programmatically compared to the initial concept of the term (before removal). If they are different, this indicates an error, either in the integration process or in the initial concept. Thus, such a term-concept pair is deemed suspicious. A study of five hierarchies of the SNOMED found 7.7% suspicious matches. A human expert needs to evaluate the correctness of suspicious concepts. In a sample of 149 of those, 19% of concepts were found to be duplicates.

Published
2010

47. Dissimilarities in the Logical Modeling of Apparently Similar Concepts in SNOMED CT

Author

Agrawal, Ankur, Elhanan, Gai, and Halper, Michael

Subjects
Humans, Systematized Nomenclature of Medicine, Articles
Abstract

Concepts whose terms are of a similar word structure are expected to have similar logical representations. Anecdotal examples from SNOMED CT indicate that this may not always be the case. An investigation into the extent of inconsistent modeling in SNOMED CT hierarchies is carried out. A lexical methodology is used to identify sets of similar concepts. It is applied to one of the most attribute-rich hierarchies, Procedure, from which a random sample of 60 sets is derived. These sets are examined in regard to hierarchical, definitional, attribute, attribute/value, and role-group aspects. Thirty percent of the sample sets were found to have at least one type of modeling inconsistency. Their presence may interfere with the performance of terminology-driven applications. With the use of SNOMED expanding, such inconsistencies may eventually affect clinical care. Due to this, external auditing should be encouraged to identify such issues and complement IHTSDO's efforts.

Published
2010

50. Rule-enforcing, Frame-based Terminology Environment for Controlled Medical Dictionaries

Author

Elhanan, Gai

Subjects
Posters
Abstract

Today's clinical information systems require efficient terminological tools. These tools must store, convey and cross-reference the content of multiple emerging standardized terminologies while at the same time support local variability. This paper proposes a frame-based, semantic network terminology environment that can reconcile coexistence of data elements from various data sources while maintaining comprehensive data integrity. The paper describes the operational rules of such a terminology environment. These, sometimes subtle, operational rules can be incorporated into user-friendly and time-responsive interfaces to facilitate maintenance tasks and enhanced utilization of the source terminologies.

Published
2002

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