News and Stories

Jan 15, 2022: With shelter-in-place continuing, Research IT team has settled down in the new remote work cluture.

Oct 30, 2021: Jose Posada, Ph. D., and Priya Desai presented two posters to showcase Research IT work.

Sep 21, 2021: We mapped several vital flowsheets and integrated the mapping in OMOP measurements table.

Sep 21, 2021: For the several years, Research IT has helped LPCH archive pediatric bedside monitoring data.

Sep 17, 2021: Ms Sonam Welekar joined us for a period of three months for an internship led by our NLP expert Dr.

Aug 21, 2021: For the last dozen years, Research IT had maintained a parallel workflow in Stanford School of Medicine (SoM) datacenter for generating a copy of SHC Clarity for research use.

May 17, 2021: In collaboration with University Privacy Office (UPO), Research IT has made five digit zipcode available in the de-identified STARR OMOP data.

March 1, 2021: Our STARR-OMOP portfolio was highlighted on Google Higher Education website.

Priya Desai, R&D Manager Biomedical Informatics, Research IT, Innovation and Translation (IaT) at TDS, and Nigam Shah, Professor of Biomedical Informatics, and Data Science at IaT are inviting you to the first ever STARR informatics summit.

Dec 15, 2020: With shelter-in-place, research pace hasn't reduced. If anything, COVID-19 may have accelerated the pace of research and increased the sense of urgency.

Oct 30, 2020: Jose Posada, Ph. D., Sr. Clinical Data Scientist from Research IT and a member of TDS Data Science team presented on Research IT's clinical text de-identification method, TiDE at the symposium collaborator showcase.

Aug 9, 2020: With the increase in Artificial Intelligence driven approaches, researchers are requesting unprecedented volumes of medical imaging data which far exceed the capacity of traditional on-premise client-server approaches for making the data research analysis-ready.

Mar 25, 2020: Our STARR manuscript is now on aRxiv. Our primary goal for the manuscript is to provide detailed information to Stanford Medicine research community so they can cite the details behind the dataset in their upcoming publications.