Mitigating Data Imbalance in Medical Report Generation Through Visual Data Resampling

Haoquan Chen, Bin Yan, Mingtao Pei*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The generation of accurate medical reports plays an important role in effective healthcare communication and precise patient treatment. However, a significant challenge arises due to the imbalanced distribution, with considerable variation of different diseases within the unhealthy data. This imbalanced data distribution hampers the learning ability of models and results in sub-optimal performance when dealing with rare diseases. In this paper, we propose BERT-VDR, a novel approach that leverages a BERT-based single-stream encoder coupled with a Visual Data Resampling (VDR) module, to mitigate the data imbalance in medical report generation. Specifically, we employ multi-label data resampling (MLSMOTE) to identify the nearest neighbors among minority-class samples and create new instances through linear interpolation. By integrating this approach with a classification task during the pre-training process, we aim to enhance the semantic precision of visual feature representations and mitigate learning performance degradation. Our method's efficacy is validated on two prominent medical imaging datasets, MIMIC-CXR and IU X-Ray. Our method clearly outperforms the baseline model and achieves state-of-the-art results across multiple metrics. Our findings highlight the potential of data resampling in enhancing medical report generation facing imbalanced data distribution.

Original languageEnglish
Title of host publicationAdvanced Intelligent Computing in Bioinformatics - 20th International Conference, ICIC 2024, Proceedings
EditorsDe-Shuang Huang, Yijie Pan, Qinhu Zhang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages255-266
Number of pages12
ISBN (Print)9789819756919
DOIs
Publication statusPublished - 2024
Event20th International Conference on Intelligent Computing, ICIC 2024 - Tianjin, China
Duration: 5 Aug 20248 Aug 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14882 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Intelligent Computing, ICIC 2024
Country/TerritoryChina
CityTianjin
Period5/08/248/08/24

Keywords

  • BERT
  • data resampling
  • medical report generatio
  • semantic precision
  • visual feature representation

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