Research Article
Open access
Published on 15 March 2024
Download pdf
Wang,W. (2024). Personalized medical recommendation system supported by medical data. Applied and Computational Engineering,45,40-46.
Export citation

Personalized medical recommendation system supported by medical data

Winston Wang *,1,
  • 1 Phillips Exeter Academy

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/45/20241024

Abstract

A personalized medical recommendation system is an intelligent system that utilizes medical data to provide targeted medical advice and services to individuals. With the lack of accumulation and development of medical data, personalized medical recommendation systems have great potential in improving medical effectiveness and saving medical resources. This article aims to explore the principles, methods, and applications of personalized medical recommendation systems based on medical data.

Keywords

Personalized Medical Recommendation System, Medical Data, Algorithms, Feature Extraction, Evaluation and Optimization, Data Security, Privacy Protection

[1]. Research on personalized search engine recommendation algorithms Chen Hua; Li Renfa; Liu Yufeng; Lianqi. Computer Application Research, 2010

[2]. Overview of evaluation methods for personalized recommendation systems Liu Jianguo; Zhou Tao; Guo Qiang; Wang Binghong. Complex Systems and Complexity Science, 2009

[3]. Research on personalized customization of Portal Liu Ying; Cai Wanjing. Computer Knowledge and Technology, 2009

[4]. Research progress in personalized recommendation systems Liu Jianguo; Zhou Tao; Wang Binghong. Progress in Natural Science, 2009

[5]. A Review of Chinese Word Segmentation Algorithms Zhang Qiyu; Zhu Ling; Zhang Yaping. Intelligence Exploration, 2008

[6]. Research on personalized services based on neural network models Xiong Ying. Modern Computer (Professional Edition), 2008

[7]. The application of Collaborative filtering technology in personalized recommendation Song Zhenzhen; Wang Hao; Yang Jing. Journal of Hefei University of Technology (Natural Science Edition), 2008

[8]. Research on personalized service user model Chen Yuan; Gou Guanglei, Computer engineering and Design, 2008

[9]. Design and implementation of personalized service recommendation system for medical information resources Zhang Wei; Mo Meiqi; Xia Zhiping; Xu Yixin. Library Magazine, 2006

[10]. Analysis and Research on User Interest Models in Intelligent Search Engines Jiang Ping, Cui Zhiming. Microelectronics and Computers, 2004

Cite this article

Wang,W. (2024). Personalized medical recommendation system supported by medical data. Applied and Computational Engineering,45,40-46.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of the 4th International Conference on Signal Processing and Machine Learning

Conference website: https://www.confspml.org/
ISBN:978-1-83558-331-9(Print) / 978-1-83558-332-6(Online)
Conference date: 15 January 2024
Editor:Marwan Omar
Series: Applied and Computational Engineering
Volume number: Vol.45
ISSN:2755-2721(Print) / 2755-273X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).