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M-US-EMRs: A Multi-modal Data Fusion Method of Ultrasonic Images and Electronic Medical Records Used for Screening of Coronary Heart Disease

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Bioinformatics Research and Applications (ISBRA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 13760))

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Abstract

Coronary heart disease (CHD) is the leading cause of death and disease burden in China and world-wide. The accurate screening for CHD can be of great value to guiding and facilitating the treatment. Traditional methods, such as computed tomography (CT) and coronary computed tomography angiography (CCTA), are costly and harmful to humans. To address these issues, we proposed a multi-modal data fusion method of ultrasonic (US) images and electronic medical records (EMRs) named M-US-EMRs model to automatically screen CHD. Comparing to traditional methods, this model features cheap, harmless to humans, easy to implement and independent of doctors. The experiment result shows that, M-US-EMRs model reached an overall classification AUC of 79.19\(\%\). Furthermore, the interpretable models that we proposed lead to an increased trust from the people who use them. Our project developed effective tools with good performance for CHD screening among a Chinese population that will help to improve the primary prevention and management of cardiovascular disease. Our method lays the groundwork for using automated interpretation to support serial patient tracking and scalable analysis of millions of ultrasonic images and EMRs archived within healthcare systems.

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Acknowledgments

This work is supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDB38050100), Shenzhen Science and Technology Program (SGDX20201103095603009).

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Authors and Affiliations

  1. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China

    Bokai Yang, Yingnan Zuo, Shunxiang Yang & Yunpeng Cai

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Bokai Yang & Yingnan Zuo

  3. Shandong University, Jinan, 250100, China

    Shunxiang Yang

  4. Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, 518060, China

    Genqiang Deng & Suisong Zhu

Authors
  1. Bokai Yang
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  2. Yingnan Zuo
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  3. Shunxiang Yang
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  4. Genqiang Deng
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  5. Suisong Zhu
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  6. Yunpeng Cai
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Corresponding author

Correspondence to Yunpeng Cai .

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Editors and Affiliations

  1. University of Connecticut, Storrs, CT, USA

    Mukul S. Bansal

  2. Georgia State University, Atlanta, GA, USA

    Zhipeng Cai

  3. University of Southern California, Los Angeles, CA, USA

    Serghei Mangul

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Yang, B., Zuo, Y., Yang, S., Deng, G., Zhu, S., Cai, Y. (2022). M-US-EMRs: A Multi-modal Data Fusion Method of Ultrasonic Images and Electronic Medical Records Used for Screening of Coronary Heart Disease. In: Bansal, M.S., Cai, Z., Mangul, S. (eds) Bioinformatics Research and Applications. ISBRA 2022. Lecture Notes in Computer Science(), vol 13760. Springer, Cham. https://doi.org/10.1007/978-3-031-23198-8_9

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  • DOI: https://doi.org/10.1007/978-3-031-23198-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23197-1

  • Online ISBN: 978-3-031-23198-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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