• 国家药监局综合司 国家卫生健康委办公厅
  • 国家药监局综合司 国家卫生健康委办公厅

An Exploration and Design of Intelligent Real-time Treatment Path Recommendation System Based on Hospital Big Data

Corresponding author: chenjianchao, 258001230@qq.com
DOI: 10.12201/bmr.202408.00055
Statement: This article is a preprint and has not been peer-reviewed. It reports new research that has yet to be evaluated and so should not be used to guide clinical practice.
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    Abstract: Purpose/Significance Optimize the patients treatment item process,shorten the waiting time and moving path in the hospital,help patients predict the time of each treatment process,and improve the patients treatment experience and hospital service efficiency. Method/Process Based on graph theory and machine learning algorithm model,the intelligent medical path recommendation model was constructed by integrating data information such as hospital spatial layout,diagnosis and treatment department distribution and patient treatment items. Based on the big data of hospital patients,the prediction model of patient treatment duration was constructed to predict the time spent in registration,waiting for treatment or examination,etc.Design and implement a real-time recommendation system for intelligent treatment paths to provide patients with clear guidance and more accurate time-consuming estimation services. Result/Conclusion The intelligent treatment path real-time recommendation system integrates the ability of treatment time prediction and path recommendation,which improves the treatment experience of patients and the service of hospitals.

    Key words: treatment time; path recommendation; treatment experience; smart hospitals

    Submit time: 26 August 2024

    Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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  • ID Submit time Number Download
    1 2024-06-11

    bmr.202408.00055V1

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jianghongjian, chenjianchao. An Exploration and Design of Intelligent Real-time Treatment Path Recommendation System Based on Hospital Big Data. 2024. biomedRxiv.202408.00055

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