Search Results for author: Jose Posada

Found 4 papers, 2 papers with code

A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records

no code implementations20 Nov 2023 Lin Lawrence Guo, Jason Fries, Ethan Steinberg, Scott Lanyon Fleming, Keith Morse, Catherine Aftandilian, Jose Posada, Nigam Shah, Lillian Sung

With continued pretraining on local data, label efficiency substantially improved, such that $FM_{SM}$ required fewer than 1% of training examples to match the fully trained GBM's performance.

Integrating Flowsheet Data in OMOP Common Data Model for Clinical Research

no code implementations16 Sep 2021 Tina Seto, Lillian Sung, Jose Posada, Priyamvada Desai, Susan Weber, Somalee Datta

Flowsheet data presents unique challenges and opportunities for integration into standardized Common Data Models (CDMs) such as the Observational Medical Outcomes Partnership (OMOP) CDM from the Observational Health Data Sciences and Informatics (OHDSI) program.

Ontology-driven weak supervision for clinical entity classification in electronic health records

1 code implementation5 Aug 2020 Jason A. Fries, Ethan Steinberg, Saelig Khattar, Scott L. Fleming, Jose Posada, Alison Callahan, Nigam H. Shah

In the electronic health record, using clinical notes to identify entities such as disorders and their temporality (e. g. the order of an event relative to a time index) can inform many important analyses.

General Classification Named Entity Recognition (NER) +3

A new paradigm for accelerating clinical data science at Stanford Medicine

1 code implementation17 Mar 2020 Somalee Datta, Jose Posada, Garrick Olson, Wencheng Li, Ciaran O'Reilly, Deepa Balraj, Joseph Mesterhazy, Joseph Pallas, Priyamvada Desai, Nigam Shah

The ecosystem is designed to bring the modern data science community to highly sensitive clinical data in a secure and collaborative big data analytics environment with a goal to enable bigger, better and faster science.

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