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Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.

J. Lemmon, L. Guo, E. Steinberg, K. Morse, S. Fleming, C. Aftandilian, S. Pfohl, J. Posada, N. Shah, J. Fries, and L. Sung. J. Am. Medical Informatics Assoc., 30 (12): 2004-2011 (November 2023)

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Humberto Luis José D' Angelo

Humberto Jorge José

Lena Posada

Nadine José Gonzalez

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Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.J. Lemmon, L. Guo, E. Steinberg, K. Morse, S. Fleming, C. Aftandilian, S. Pfohl, J. Posada, N. Shah, J. Fries and 1 other author(s). J. Am. Medical Informatics Assoc., 30 (12): 2004-2011 (November 2023)A new paradigm for accelerating clinical data science at Stanford Medicine.S. Datta, J. Posada, G. Olson, W. Li, C. O'Reilly, D. Balraj, J. Mesterhazy, J. Pallas, P. Desai, and N. Shah. CoRR, (2020)Integrating Flowsheet Data in OMOP Common Data Model for Clinical Research.T. Seto, L. Sung, J. Posada, P. Desai, S. Weber, and S. Datta. CoRR, (2021)Electrochemical Immunosensor for the Quantification of S100B at Clinically Relevant Levels Using a Cysteamine Modified Surface.A. Rodríguez, F. Burgos-Flórez, J. Posada, E. Cervera, V. Zucolotto, H. Sanjuán, M. Sanjuan, and P. Villalba. Sensors, 21 (6): 1929 (2021)Fault detection at a continuous hot dip galvanization line.J. Posada, J. Garcia, M. Torres, and M. Sanjuan. LARC, page 1-4. IEEE, (2011)Characterizing database granularity using SNOMED-CT hierarchy.A. Ostropolets, C. Reich, P. Ryan, C. Weng, A. Molinaro, F. DeFalco, J. Jonnagaddala, S. Liaw, H. Jeon, R. Park and 9 other author(s). AMIA, AMIA, (2020)Social Context Sentence Classification from Psychiatric Reports using Positive and Unlabeled Learning.J. Posada, L. Shi, S. Castro, S. Visweswaran, N. Ryan, H. Harkema, and R. Tsui. AMIA, AMIA, (2018)A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records.L. Guo, J. Fries, E. Steinberg, S. Fleming, K. Morse, C. Aftandilian, J. Posada, N. Shah, and L. Sung. CoRR, (2023)Measuring quality-of-care in treatment of young children with attention-deficit/hyperactivity disorder using pre-trained language models.M. Pillai, J. Posada, R. Gardner, T. Hernandez-Boussard, and Y. Bannett. J. Am. Medical Informatics Assoc., 31 (4): 949-957 (2024)BigBio: A Framework for Data-Centric Biomedical Natural Language Processing.J. Fries, L. Weber, N. Seelam, G. Altay, D. Datta, S. Garda, S. Kang, R. Su, W. Kusa, S. Cahyawijaya and 33 other author(s). NeurIPS, (2022)

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Disambiguation of "Posada, José D."

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Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.

Please choose a person to relate this publication to

Humberto Luis José D' Angelo

Humberto Luis José D' Angelo

Humberto Jorge José

Lena Posada

Nadine José Gonzalez

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Posada, José D."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.

Please choose a person to relate this publication to

Humberto Luis José D' Angelo

Humberto Luis José D' Angelo

Humberto Jorge José

Lena Posada

Nadine José Gonzalez

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
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Chicago
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Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.