Lillian Sung

According to our database, Lillian Sung authored at least 11 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare.

Lin Lawrence Guo, Keith E. Morse, Catherine Aftandilian, Ethan Steinberg, Jason Alan Fries, José D. Posada, Scott Lanyon Fleming, Joshua Lemmon, Karim Jessa, Nigam Shah, Lillian Sung

BMC Medical Informatics Decis. Mak., December, 2024

2023

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

Joshua Lemmon, Lin Lawrence Guo, Ethan Steinberg, Keith E. Morse, Scott Lanyon Fleming, Catherine Aftandilian, Stephen R. Pfohl, José D. Posada, Nigam Shah, Jason Alan Fries, Lillian Sung

J. Am. Medical Informatics Assoc., November, 2023

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

Lin Lawrence Guo, Jason A. Fries, Ethan Steinberg, Scott Lanyon Fleming, Keith E. Morse, Catherine Aftandilian, José D. Posada, Nigam Shah, Lillian Sung

CoRR, 2023

2022

Machine learning approaches to investigate <i>Clostridioides difficile</i> infection and outcomes: A systematic review.

Yujie Chen, Min Xi, Alistair E. W. Johnson, George Tomlinson, Aaron Campigotto, Lingxiao Chen, Lillian Sung

Int. J. Medical Informatics, 2022

Real-World Data at the Point-of-Care: Exploring Education Needs Across All Stakeholders.

Julian Genkins, Dev Dash, Lillian Sung, Saurabh Gombar, Alison Callahan

Proceedings of the AMIA 2022, 2022

2021

Integrating Flowsheet Data in OMOP Common Data Model for Clinical Research.

Tina Seto, Lillian Sung, José D. Posada, Priyamvada Desai, Susan Weber, Somalee Datta

CoRR, 2021

Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.

Lin Lawrence Guo, Stephen R. Pfohl, Jason Alan Fries, José D. Posada, Scott L. Fleming, Catherine Aftandilian, Nigam Shah, Lillian Sung

Appl. Clin. Inform., 2021

Data Quality of Chemotherapy-Induced Nausea and Vomiting Documentation.

Melissa Beauchemin, Chunhua Weng, Lillian Sung, Adrienne Pichon, Maura Abbott, Dawn L. Hershman, Rebecca Schnall

Appl. Clin. Inform., 2021

A Retrospective Analysis of Machine Learning Driven Antibiotic Selection in the Emergency Department.

Conor K. Corbin, Arhana Chattopadhyah, Lillian Sung, Amy Chang, Stan Deresinski, Jonathan H. Chen

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2019

Initial development of Supportive care Assessment, Prioritization and Recommendations for Kids (SPARK), a symptom screening and management application.

Sadie Cook, Emily Vettese, Dilip Soman, Shannon Hyslop, Susan Kuczynski, Brenda Spiegler, Hailey Davis, Nathan Duong, Stacee Ou Wai, Robert Golabek, Patryk Golabek, Adam Antoszek-Rallo, Tal Schechter, L. Lee Dupuis, Lillian Sung

BMC Medical Informatics Decis. Mak., 2019

Clinical decision support for therapeutic decision-making in cancer: A systematic review.

Melissa Beauchemin, Meghan T. Murray, Lillian Sung, Dawn L. Hershman, Chunhua Weng, Rebecca Schnall

Int. J. Medical Informatics, 2019