1 code implementation • 24 Jun 2024 • Yeonsu Kwon, Jiho Kim, Gyubok Lee, Seongsu Bae, Daeun Kyung, Wonchul Cha, Tom Pollard, Alistair Johnson, Edward Choi
To address this, we developed EHRCon, a new dataset and task specifically designed to ensure data consistency between structured tables and unstructured notes in EHRs.
1 code implementation • 4 May 2024 • Gyubok Lee, Sunjun Kweon, Seongsu Bae, Edward Choi
In this paper, we describe the task of reliable text-to-SQL modeling, the dataset, and the methods and results of the participants.
3 code implementations • NeurIPS 2023 • Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, JungWoo Oh, Lei Ji, Eric I-Chao Chang, Tackeun Kim, Edward Choi
To develop our dataset, we first construct two uni-modal resources: 1) The MIMIC-CXR-VQA dataset, our newly created medical visual question answering (VQA) benchmark, specifically designed to augment the imaging modality in EHR QA, and 2) EHRSQL (MIMIC-IV), a refashioned version of a previously established table-based EHR QA dataset.
1 code implementation • 1 Sep 2023 • Sunjun Kweon, Junu Kim, Jiyoun Kim, Sujeong Im, Eunbyeol Cho, Seongsu Bae, JungWoo Oh, Gyubok Lee, Jong Hak Moon, Seng Chan You, Seungjin Baek, Chang Hoon Han, Yoon Bin Jung, Yohan Jo, Edward Choi
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 privacy regulations.
no code implementations • 10 Jul 2023 • Gangwoo Kim, Hajung Kim, Lei Ji, Seongsu Bae, Chanhwi Kim, Mujeen Sung, Hyunjae Kim, Kun Yan, Eric Chang, Jaewoo Kang
In this paper, we introduce CheXOFA, a new pre-trained vision-language model (VLM) for the chest X-ray domain.
1 code implementation • NeurIPS 2023 • JungWoo Oh, Gyubok Lee, Seongsu Bae, Joon-Myoung Kwon, Edward Choi
As a result, our dataset includes diverse ECG interpretation questions, including those that require a comparative analysis of two different ECGs.
1 code implementation • NeurIPS 2022 Datasets and Benchmarks 2022 • Gyubok Lee, Hyeonji Hwang, Seongsu Bae, Yeonsu Kwon, Woncheol Shin, Seongjun Yang, Minjoon Seo, Jong-Yeup Kim, Edward Choi
We then manually linked these questions to two open-source EHR databases, MIMIC-III and eICU, and included various time expressions and held-out unanswerable questions in the dataset, which were also collected from the poll.
1 code implementation • 18 Mar 2022 • Sungjin Park, Seongsu Bae, Jiho Kim, Tackeun Kim, Edward Choi
MedGTX uses a novel graph encoder to exploit the graphical nature of structured EHR data, and a text encoder to handle unstructured text, and a cross-modal encoder to learn a joint representation space.
1 code implementation • 14 Mar 2022 • Daeyoung Kim, Seongsu Bae, Seungho Kim, Edward Choi
In addition, for a reliable EHR-QA model, we apply the uncertainty decomposition method to measure the ambiguity in the input question.
no code implementations • 14 Nov 2021 • Seongsu Bae, Daeyoung Kim, Jiho Kim, Edward Choi
An intelligent machine that can answer human questions based on electronic health records (EHR-QA) has a great practical value, such as supporting clinical decisions, managing hospital administration, and medical chatbots.