Abstract Number:
1666
Submission Type:
Topic-Contributed Paper Session
Participants:
Anru Zhang (1), Chuan Hong (2), Benjamin Goldstein (1), Rui Zhang (3), Rui Duan (2), Dandan Liu (4)
Institutions:
(1) Duke University, N/A, (2) N/A, N/A, (3) University of Minnesota, MN, (4) Vanderbilt University Medical Center, N/A
Chair:
Session Organizer:
Speaker(s):
Session Description:
Electronic Health Records (EHR) have transformed modern healthcare by providing a wealth of patient information. The analysis of EHR data is instrumental in uncovering valuable insights, guiding medical decisions, and improving patient care. We are submitting this session proposal to the Joint Statistical Meeting 2024 to bring together experts and researchers at the forefront of statistical innovation in EHR data analysis. We have assembled four speakers for this session, representing diverse expertise from the fields of medical informatics, biostatistics, and statistics:
Benjamin Goldstein is currently an Associate Professor of Biostatistics & Bioinformatics at Duke University, joint with the Duke Clinical Research Institute and the Children's Health & Discovery Initiative. He holds secondary appointments in the Department of Pediatrics and Population Health. His research interests are in the meaningful use of Electronic Health Records data. My work sits at the intersection of Biostatistics, Biomedical Informatics, Epidemiology, and Machine Learning. He collaborates actively with both clinicians and fellow methodologists. He tentatively brings us "Comparing Natural Language Processing and Structured Medical Data to Develop a Computable Phenotype for Patients Hospitalized Due to COVID-19: Retrospective Analysis."
Rui Zhang is the Founding Chief of Division of Computational Health Sciences and Associate Professor in the Department of Surgery at the University of Minnesota School of Medicine. He is a McKnight Presidential Fellow and the Director of NLP/IE research program. He is Scientific Co-Director of Innovative Methods & Data Science program in the Center for Learning Health Systems Science. Dr. Zhang is a graduate faculty in Data Science, BICB and SAPh graduate programs. His research interests are clinical natural language processing, text mining, literature-based discovery, complementary and alternative medicine informatics, machine learning, and statistic analysis. His research has been supported by NCCIH, NIA, ODS, AHRQ and Medtronic. His tentative talk talk is on "Language models on EHR data for clinical research."
Rui Duan is an Assistant Professor of Biostatistics at the Harvard T.H. Chan School of Public Health, and also a primary faculty member at the Department of Epidemiology and Harvard Data Science Initiative. Her research focuses on developing statistical and machine learning methods for effective use of biomedical data to support precise and accurate diagnostics, individualized treatments, and improve patient outcomes. Her talk will be on "Federated Learning Methods for Phenotyping Across Multi-Site Electronic Health Records (EHRs)."
Dandan Liu is an Associate Professor of Biostatistics at Vanderbilt University, currently serving as the Director of the Vanderbilt Institute for Clinical and Translational Research (VICTR) Methods Program. She holds the position of Co-director at the Vanderbilt Biostatistics Data Coordinating Center (VBDCC). Her primary research interests include biomarker evaluation, event history data analysis, and risk prediction modeling. Her expertise particularly shines in the application of critical health issues such as cardiovascular disease, cancer, and Alzheimer's disease, as well as in the utilization of electronic health records for disease progression modeling. Her talk will be on "Statistical Challenges of Implementing an EHR-based Prediction Model in Real Time."
Sponsors:
Biometrics Section 2
International Chinese Statistical Association 1
Section on Statistical Computing 3
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
Yes
Applied
Yes
Estimated Audience Size
Small (<80)
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
I understand