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MANDY: Towards a Smart Primary Care Chatbot Application

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Knowledge and Systems Sciences (KSS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 780))

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Abstract

The paper reports on a proof-of-concept of \(\mathsf {Mandy}\), a primary care chatbot system created to assist healthcare staffs by automating the patient intake process. The chatbot interacts with a patient by carrying out an interview, understanding their chief complaints in natural language, and submitting reports to the doctors for further analysis. The system provides a mobile-app front end for the patients, a diagnostic unit, and a doctor’s interface for accessing patient records. The diagnostic unit consists of three main modules: An analysis engine for understanding patients symptom descriptions, a symptom-to-cause mapper for reasoning about potential causes, and a question generator for deriving further interview questions. The system combines data-driven natural language processing capability with knowledge-driven diagnostic capability. We evaluate our proof-of-concept on benchmark case studies and compare the system with existing medical chatbots.

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Notes

  1. 1.

    http://www.bbc.com/news/technology-36528253.

  2. 2.

    https://deepmind.com/applied/deepmind-health/, 2017.

  3. 3.

    https://www.ibm.com/watson/health/, 2017.

  4. 4.

    http://research.baidu.com/baidus-melody-ai-powered-conversational-bot-doctors-patients/, 2016.

  5. 5.

    http://www.imore.com/siri.

  6. 6.

    https://www.microsoft.com/en/mobile/experiences/cortana/.

  7. 7.

    Florence Bot, https://florence.chat/.

  8. 8.

    Your.MD, https://www.your.md/.

  9. 9.

    HealthTap, https://www.healthtap.com/.

  10. 10.

    https://aws.amazon.com/.

  11. 11.

    https://github.com/lni600/Mandy.git.

  12. 12.

    http://13.54.91.140:8080/HealthWebApp/ To log in, the user needs to input ‘admin’ as both Username and Password.

  13. 13.

    E.g. online databases such as http://www.diseasesdatabase.com.

  14. 14.

    https://en.wikipedia.org/.

  15. 15.

    http://www.healthline.com/.

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Acknowledgement

The first author is partially funded by a scholarship offered by Precision Driven Health in New Zealand, a public-private research partnership aimed at improving health outcomes through data science. Initial progress of theresearch was reported in the PDH & Orion Health Blog https://orionhealth.com/ global/knowledge-hub/blogs/meet-mandy-an-intelligent-and-interactive-medic are-system/.

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Authors and Affiliations

  1. Department of Computer Science, The University of Auckland, Auckland, New Zealand

    Lin Ni, Chenhao Lu, Niu Liu & Jiamou Liu

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  1. Lin Ni
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  2. Chenhao Lu
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  3. Niu Liu
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  4. Jiamou Liu
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Corresponding author

Correspondence to Lin Ni .

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Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jian Chen

  2. Thammasat University, Bangkadi Muang Pathumthani, Thailand

    Thanaruk Theeramunkong

  3. National Electronics and Computer Technology Center, Pathumthani, Thailand

    Thepachai Supnithi

  4. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China

    Xijin Tang

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Ni, L., Lu, C., Liu, N., Liu, J. (2017). MANDY: Towards a Smart Primary Care Chatbot Application. In: Chen, J., Theeramunkong, T., Supnithi, T., Tang, X. (eds) Knowledge and Systems Sciences. KSS 2017. Communications in Computer and Information Science, vol 780. Springer, Singapore. https://doi.org/10.1007/978-981-10-6989-5_4

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  • DOI: https://doi.org/10.1007/978-981-10-6989-5_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6988-8

  • Online ISBN: 978-981-10-6989-5

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