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Sim, Ida

0000-0002-1045-8459

Mayo Clinic

University of California, San Francisco

Citations 3

Paging the Clinical Informatics Community: Respond STAT to Dobbs v. Jackson's Women's Health Organization
Ravi, Akshay , Weia, Benjamin , Aarts, Jos , Ahmad, Hasan B., Araj, Ellen, Bauml, Julie A., Boyd, Andrew D. , Brecht-Doscher, Aimee, Butler‐Henderson, Kerryn , Butte, Atul J. , Cardilo, Anthony B., Chilukuri, Nymisha , Cho, Mildred K. , Cohen, Jenny K., Craven, Catherine K. , Crusco, Salvatore, Dadabhoy, Farah Z. , Dash, Dev , DeBolt, Claire , Fayanju, Oluseyi A, Fochtmann, Laura J. , Graham, Justin V., Hanna, John , Hofford, Mackenzie , Hron, Jonathan D. , Huang, Sean S, Jackson, Brian R. , Kaplan, Bonnie , Kelly, William R. , Ko, Kyungmin, Kurapati, Nikhil , Labbad, Gabriel , Lee, Julie , Leitner, Stefano, Liao, Zachary C , Melnick, Edward R. , Muniyappa, Anoop , Murray, Sara G. , Nichols-Johnson, Victoria, Novak, Laurie L. , Ogan, William Scott , Ozeran, Larry, Pageler, Natalie M. , Pandita, Deepti , Perumbeti, Ajay, Petersen, Carolyn , Pierce, Logan , Puttagunta, Raghuveer, Ramaswamy, Priya , Rogers, Kendall, Ryan, Angela M., Sarabu, Chethan , Shaw, Kate A. , Spector, Jacob D. , Starren, Justin , Stoffel, Michelle , Swanson, Karl , Tomes, Adrian, Unertl, Kim M. , Weon, Jenny L. , Wiley, Kevin , Winkelstein, Peter , Wong, Jenson, Xie, James , Yarahuan, Julia , Yung, Nathan , Zera, Chloe , Sadasivaiah, Shobha , Boyd, Andrew D , Melnick, Edward R , Petersen, Carolyn , Arvisais‐Anhalt, Simone , Benham‐Hutchins, Marge , Brecht-Doscher, Aimee, Elkin, Peter L. , Hersh, William , Kelly, William, Koppel, Ross , Lehmann, Christoph U. , Medford, Richard J , Neinstein, Aaron Barak , Rosenbloom, S. Trent , Ryan, Angela, Saleh, Sameh Nagui , Schreiber, Richard , Sim, Ida , Sirintrapun, Sahussapont Joseph , Solomonides, Anthony , Subbian, Vignesh , Trang, Karen , Whooley, Mary A. , Williamson, Drew F. K. , Ratanawongsa, Neda

Applied Clinical Informatics | December 19, 2022 | Volume: 14 | Issue: 01 | Pages: 164-171

10.1055/a-2000-7590 Get It

Keeping Raw Data in Context
Nagarajan, Rakesh, Nahm, Meredith, Sim, Ida , Chute, Christopher G. , Lehmann, Harold P. , Scheuermann, Richard H.

Science | February 7, 2009 | Volume: 323 | Issue: 5915 | Pages: 713-713

10.1126/science.323.5915.713a Get It

National Center for Biomedical Ontology: Advancing Biomedicine through Structured Organization of Scientific Knowledge
Lewis, Suzanna , Mungall, Chris , Misra, Sima, Westerfield, Monte , Ashburner, Michael , Solbrig, Harold R. , Storey, Margaret‐Anne , Smith, Barry , Day-Richter, John, Noy, Natalya F., Musen, Mark A. , Rubin, Daniel L. , Sim, Ida , Chute, Christopher G. , Mungall, Christopher J

OMICS: A Journal of Integrative Biology | August 10, 2006 | Volume: 10 | Issue: 2 | Pages: 185-198

10.1089/omi.2006.10.185 Get It

The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease. This paper is part of the special issue of OMICS on data standards.