Seongsu Bae

According to our database1, Seongsu Bae authored at least 10 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records.
CoRR, 2024

Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Overview of the EHRSQL 2024 Shared Task on Reliable Text-to-SQL Modeling on Electronic Health Records.
Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024

2023
ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

KU-DMIS-MSRA at RadSum23: Pre-trained Vision-Language Model for Radiology Report Summarization.
Proceedings of the 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, 2023

2022
EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graph-Text Multi-Modal Pre-training for Medical Representation Learning.
Proceedings of the Conference on Health, Inference, and Learning, 2022

Uncertainty-Aware Text-to-Program for Question Answering on Structured Electronic Health Records.
Proceedings of the Conference on Health, Inference, and Learning, 2022

2021
Question Answering for Complex Electronic Health Records Database using Unified Encoder-Decoder Architecture.
Proceedings of the Machine Learning for Health, 2021


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