13 citations · 32 across the 12 of their papers we have counts for
5 papers · 1 filter
EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images
Seongsu Bae, Daeun Kyung, Jaehee Ryu +8
Electronic Health Records (EHRs), which contain patients' medical histories in various multi-modal formats, often overlook the potential for joint reasoning across imaging and tabl…
Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes
Sunjun Kweon, Junu Kim, Jiyoun Kim +12
The development of large language models tailored for handling patients' clinical notes is often hindered by the limited accessibility and usability of these notes due to strict pr…
KU-DMIS-MSRA at RadSum23: Pre-trained Vision-Language Model for Radiology Report Summarization
Gangwoo Kim, Hajung Kim, Lei Ji +7
In this paper, we introduce CheXOFA, a new pre-trained vision-language model (VLM) for the chest X-ray domain. Our model is initially pre-trained on various multimodal datasets wit…
ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram
Jungwoo Oh, Gyubok Lee, Seongsu Bae +2
Question answering (QA) in the field of healthcare has received much attention due to significant advancements in natural language processing. However, existing healthcare QA datas…
EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records
Gyubok Lee, Hyeonji Hwang, Seongsu Bae +6
We present a new text-to-SQL dataset for electronic health records (EHRs). The utterances were collected from 222 hospital staff members, including physicians, nurses, and insuranc…