7 citations · 9 across the 4 of their papers we have counts for
4 papers
CURENet: Combining Unified Representations for Efficient Chronic Disease Prediction
Cong-Tinh Dao, Nguyen Minh Thao Phan, Jun-En Ding +12
Electronic health records (EHRs) are designed to synthesize diverse data types, including unstructured clinical notes, structured lab tests, and time-series visit data. Physicians…
Representation Learning of Lab Values via Masked AutoEncoders
David Restrepo, Chenwei Wu, Yueran Jia +5
Accurate imputation of missing laboratory values in electronic health records (EHRs) is critical to enable robust clinical predictions and reduce biases in AI systems in healthcare…
MEDFuse: Multimodal EHR Data Fusion with Masked Lab-Test Modeling and Large Language Models
Thao Minh Nguyen Phan, Cong-Tinh Dao, Chenwei Wu +7
Electronic health records (EHRs) are multimodal by nature, consisting of structured tabular features like lab tests and unstructured clinical notes. In real-life clinical practice,…
Efficient In-Context Medical Segmentation with Meta-driven Visual Prompt Selection
Chenwei Wu, David Restrepo, Zitao Shuai +2
In-context learning (ICL) with Large Vision Models (LVMs) presents a promising avenue in medical image segmentation by reducing the reliance on extensive labeling. However, the ICL…