Blog

The 2024 AMIA (American Medical Informatics Association) Annual Symposium will take place in San Francisco from November 9 through November 13. Department members with work to be presented at the symposium include:

Saturday, November 9

Workshop 17, "REDCap on FHIR: Implementing and Using Clinical Data Interoperability Services" - professor Paul Harris, co-instructor/author

Sunday, November 10

Workshop 27, "Advancing Biomedical Research Using Multi-omics Data in the All of Us Researcher Workbench,"  8:30 am - co-authored by Paul Harris

Session 7, "Pediatric Health Informatics - Kid Coders,"  3:30 pm

"Revealing Patterns of Child Maltreatment Policy Differences and Demographic Dynamics using BERT-Networks and Clustering Approach" - co-authored by associate professor Rameela Raman 

Monday, November 11

Session 17, "LIEAF: Artificial Intelligence and Data Science in Health Informatics Education," 8:30 am

Enhancing Causes of Death Prediction from Electronic Health Records through Multi-Modal Integration of Structured and Unstructured EHR Data - co-authored by professor Michael Matheny

Session 22, "AI Fairness and Ethics - Justice League," 8:30 am

• "Fairness of AI Collaboration and Suppression in Emergency Triage" - co-authored by professor Bradley Malin
• "Enhancement of Fairness in AI for Chest X-ray Classification" - co-authored by Bradley Malin

Session 53, "Utilization Data and Data Utilization - Auditory Audits, Listening to the Data," 3:30 pm

"Optimizing Large Language Models for Discharge Prediction: Best Practices in Leveraging Electronic Health Record Audit Logs" - co-authored by Bradley Malin

Session 54, "Patient Generated Data - Organic Certified," 3:30 pm

"Examining Oral Anti-Cancer Medication Continuation Using Questionnaires, Prescription Refills, and Structured Electronic Health Records" - co-authored by professor Qingxia Chen, Bradley Malin, and alumnus Zhijun Yin (MS 2017)

Poster session 1, 5:00 pm

P114: "Machine Learning Methods for Estimating Gestational Age at Birth from Electronic Health Records" - co-authored by professor Leena Choi

P118: "Large Language Models Enhance the Identification of Emergency Department Visits for Symptomatic Kidney Stones" - co-authored by PhD candidate Siwei Zhang and assistant professor Yaomin Xu

P171: "Comparing EHR-recorded Race/Ethnicity to Self-reported Race/Ethnicity: Insights from the All of Us Research Program" - coauthored by Xiaoke (Sarah) Feng (first author), biostatistician Andrew Guide, assistant in biostatistics Shawn Garbett, and Qingxia Chen

Tuesday, November 12

Session 98, "Wearable Sensor Data - Data on the Go," 3:30 pm

"'I worry we’ll blow right by it': Barriers to Uptake of the STRATIFY CDSS for ED Discharge in Acute Heart Failure" - co-authored by associate professor Dandan Liu

Poster session 2, 5:00 pm

P05: "Utilizing Large Language Models (LLM) to Optimize Domain-Specific Natural Language Processing (NLP) for Identifying Patients with No Reason for Not Prescribing ACEI/ARB in Chronic Kidney Disease (CKD) Management" - co-authored by Michael Matheny

P27: "Assessing ChatGPT Responses to Alzheimer’s Disease Myths" - co-authored by Bradley Malin and Zhijun Yin

P117: "Algorithmic Matching of Unique Device Information to Electronic Health Record Data" - co-authored by Michael Matheny

P178: "A Study of Challenges In Algorithmic Transportability Between VHA Sites" - co-authored by Michael Matheny

P188: "Real-Time Automated Billing for Tobacco Treatment: A CDS Hook Approach for Simulating Clinician Facing Coding Prompts Within EHRs" - co-authored by Michael Matheny

Wednesday, November 13

Session 102, "Self-Service Software Tools for Clinical and Translational Research: Rationale, Benefits, Limitations, Challenges, and the Future," 8:00 am - Paul Harris, speaker

Updated 11.11.2024 to include P01.

The 2024 Women in Statistics and Data Science Conference is underway in Reston, Virginia, from October 16 through 18. We are proud of the department members and alumni involved with this year's meeting. They include:

MS student Zongyue Teng

• First and presenting author of "Going for gold: Using record linkage and Bayesian hierarchical modeling to select winning gymnasts at the 2024 Paris Olympics" (speed session Wednesday, poster Thursday; graphic via WakeForestStats)

Sarah Lotspeich (PhD 2021)

• Co-author of "Quantifying the impact of measurement error on health disparities models" (speed session Wednesday, poster Thursday)
• Organizer of and speaker in "Mastering Data: Insights into Master's Degrees in Statistics and Analytics" (panel, Thursday)
• Organizer of "More than Statistics: Improving Maternal and Infant Health with Data" (invited session, Thursday)
• Co-author of "Adjusting for covariate misclassification to quantify the relationship between diabetes and local access to healthy food" (speed session 3, Thursday)
• Co-organizer of and speaker in "Statistical Methods For HIV Research: Battling An Epidemic With Linked, Missing, And Error-prone Data" (invited session, Thursday)
• Panelist for "Statistical Storytelling: Insights Into Effective Presentation Strategies" (Friday)
• Organizer of "Cause For Celebration: Adapting Causal Inference Methods For Challenging Datasets" (invited session, Friday)

PhD student Ashley Mullan

• First and presenting author of "Adjusting for covariate misclassification to quantify the relationship between diabetes and local access to healthy food" (speed session and poster, Thursday)
• Chair of and panelist for "Statistical Storytelling: Insights Into Effective Presentation Strategies" (Friday)

Lead biostatistician Amy Perkins

• First and presenting author of "Machine Learning Model Robustness and Performance Stability in Future Years when Predicting Adverse Events in a Veteran Population and a Diabetic Subpopulation" (speed session and poster, Thursday). Co-authors include assistant professor Amber Hackstadt and professor Michael Matheny.

Lucy D'Agostino McGowan (PhD 2018):

• Speaker in "Statistical Methods for Missing Data Imputation" (panel, Thursday)
• Co-organizer of "Statistical Methods For HIV Research: Battling An Epidemic With Linked, Missing, And Error-prone Data" (invited session, Thursday)
• Panelist for "Statistical Storytelling: Insights Into Effective Presentation Strategies" (Friday)
• Speaker in "Cause For Celebration: Adapting Causal Inference Methods For Challenging Datasets" (invited session, Friday)