Medical Diagnosis by Complaints of Patients and Machine Learning

Gangmin Li; Haowei Song; Hai Ning Liang; Yuanying Qu; Lu Liu; Xuming Bai

doi:10.1109/CISP-BMEI48845.2019.8965949

Medical Diagnosis by Complaints of Patients and Machine Learning

Gangmin Li, Haowei Song, Hai Ning Liang, Yuanying Qu, Lu Liu, Xuming Bai

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

2 Citations (Scopus)

Abstract

Self-diagnose becomes an important research topic and hot web application. It relies on patients' own description about their conditions. Finding relationship between patients' complain and the possible diseases is the key. This paper reports our efforts on applying machine learning models to solve this problem. We firstly collected and build a dataset including 10,000 chief complaints from authoritative medical websites including haodf.com, and yyk.99.com and top Chinese hospitals. We then trained Support Vector Machine (SVM) and Bidirectional Long and Short-term Memory (BiLSTM) models using our collected dataset to verify our dataset and to test prediction models. The test shows the models trained with sample datasets have a stable performance with 75% in accuracy, 81% in precision and recall being 81%.

Original language	English
Title of host publication	Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
Editors	Qingli Li, Lipo Wang
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728148526
DOIs	https://doi.org/10.1109/CISP-BMEI48845.2019.8965949
Publication status	Published - Oct 2019
Event	12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 - Huaqiao, China Duration: 19 Oct 2019 → 21 Oct 2019

Publication series

Name	Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

Conference

Conference	12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
Country/Territory	China
City	Huaqiao
Period	19/10/19 → 21/10/19

Keywords

BiLSTM
SVM
chief complaint corpus
disease diagnosis

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10.1109/CISP-BMEI48845.2019.8965949

Cite this

Li, G., Song, H., Liang, H. N., Qu, Y., Liu, L., & Bai, X. (2019). Medical Diagnosis by Complaints of Patients and Machine Learning. In Q. Li, & L. Wang (Eds.), Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 Article 8965949 (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISP-BMEI48845.2019.8965949

Li, Gangmin ; Song, Haowei ; Liang, Hai Ning et al. / Medical Diagnosis by Complaints of Patients and Machine Learning. Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019. editor / Qingli Li ; Lipo Wang. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019).

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title = "Medical Diagnosis by Complaints of Patients and Machine Learning",

abstract = "Self-diagnose becomes an important research topic and hot web application. It relies on patients' own description about their conditions. Finding relationship between patients' complain and the possible diseases is the key. This paper reports our efforts on applying machine learning models to solve this problem. We firstly collected and build a dataset including 10,000 chief complaints from authoritative medical websites including haodf.com, and yyk.99.com and top Chinese hospitals. We then trained Support Vector Machine (SVM) and Bidirectional Long and Short-term Memory (BiLSTM) models using our collected dataset to verify our dataset and to test prediction models. The test shows the models trained with sample datasets have a stable performance with 75% in accuracy, 81% in precision and recall being 81%.",

keywords = "BiLSTM, SVM, chief complaint corpus, disease diagnosis",

author = "Gangmin Li and Haowei Song and Liang, {Hai Ning} and Yuanying Qu and Lu Liu and Xuming Bai",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 ; Conference date: 19-10-2019 Through 21-10-2019",

year = "2019",

month = oct,

doi = "10.1109/CISP-BMEI48845.2019.8965949",

language = "English",

series = "Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Li, G, Song, H, Liang, HN, Qu, Y, Liu, L & Bai, X 2019, Medical Diagnosis by Complaints of Patients and Machine Learning. in Q Li & L Wang (eds), Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019., 8965949, Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019, Institute of Electrical and Electronics Engineers Inc., 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019, Huaqiao, China, 19/10/19. https://doi.org/10.1109/CISP-BMEI48845.2019.8965949

Medical Diagnosis by Complaints of Patients and Machine Learning. / Li, Gangmin; Song, Haowei; Liang, Hai Ning et al.
Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019. ed. / Qingli Li; Lipo Wang. Institute of Electrical and Electronics Engineers Inc., 2019. 8965949 (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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AU - Li, Gangmin

AU - Song, Haowei

AU - Liang, Hai Ning

AU - Qu, Yuanying

AU - Liu, Lu

AU - Bai, Xuming

PY - 2019/10

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N2 - Self-diagnose becomes an important research topic and hot web application. It relies on patients' own description about their conditions. Finding relationship between patients' complain and the possible diseases is the key. This paper reports our efforts on applying machine learning models to solve this problem. We firstly collected and build a dataset including 10,000 chief complaints from authoritative medical websites including haodf.com, and yyk.99.com and top Chinese hospitals. We then trained Support Vector Machine (SVM) and Bidirectional Long and Short-term Memory (BiLSTM) models using our collected dataset to verify our dataset and to test prediction models. The test shows the models trained with sample datasets have a stable performance with 75% in accuracy, 81% in precision and recall being 81%.

AB - Self-diagnose becomes an important research topic and hot web application. It relies on patients' own description about their conditions. Finding relationship between patients' complain and the possible diseases is the key. This paper reports our efforts on applying machine learning models to solve this problem. We firstly collected and build a dataset including 10,000 chief complaints from authoritative medical websites including haodf.com, and yyk.99.com and top Chinese hospitals. We then trained Support Vector Machine (SVM) and Bidirectional Long and Short-term Memory (BiLSTM) models using our collected dataset to verify our dataset and to test prediction models. The test shows the models trained with sample datasets have a stable performance with 75% in accuracy, 81% in precision and recall being 81%.

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BT - Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

A2 - Li, Qingli

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Li G, Song H, Liang HN, Qu Y, Liu L, Bai X. Medical Diagnosis by Complaints of Patients and Machine Learning. In Li Q, Wang L, editors, Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8965949. (Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019). doi: 10.1109/CISP-BMEI48845.2019.8965949

Medical Diagnosis by Complaints of Patients and Machine Learning

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