International Journal of Internet, Broadcasting and Communication

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
권호 표지
DOI QR코드

DOI QR Code

Design and Implementation of Intelligent Medical Service System Based on Classification Algorithm

  • Yu, Linjun (School of Electronic Commerce, Jiujiang University) ;
  • Kang, Yun-Jeong (College of Convergence Liberal Arts, Wonkwang University) ;
  • Choi, Dong-Oun (Department of Computer Software Engineering, Wonkwang University)
  • Received : 2021.06.23
  • Accepted : 2021.07.03
  • Published : 2021.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

With the continuous acceleration of economic and social development, people gradually pay attention to their health, improve their living environment, diet, strengthen exercise, and even conduct regular health examination, to ensure that they always understand the health status. Even so, people still face many health problems, and the number of chronic diseases is increasing. Recently, COVID-19 has also reminded people that public health problems are also facing severe challenges. With the development of artificial intelligence equipment and technology, medical diagnosis expert systems based on big data have become a topic of concern to many researchers. At present, there are many algorithms that can help computers initially diagnose diseases for patients, but they want to improve the accuracy of diagnosis. And taking into account the pathology that varies from person to person, the health diagnosis expert system urgently needs a new algorithm to improve accuracy. Through the understanding of classic algorithms, this paper has optimized it, and finally proved through experiments that the combined classification algorithm improved by latent factors can meet the needs of medical intelligent diagnosis.

Keywords

Acknowledgement

This paper was supported by the research grant of the Wonkwang University in 2021

References

  1. U. M. Fayyad. Knowledge Discovery in Databases: An Overview[C]. International Workshop on Inductive Logic Programming. Springer-Verlag, 1997, 3-16
  2. Liu Peiqi. Development technology and application of a new generation of expert system[M]. Xi'an: Xidian University Press, 2014, 51-90[41].
  3. Emken B A, Li M, Thatte G, et al. Recognition of physical activities in overweight hispanic youth using KNOWME Net-works[J]. Journal of Physical Activity & Health,2012, 9(3):432-441. https://doi.org/10.1123/jpah.9.3.432
  4. Rodriguez-Villegas E, Chen G, Radcliffe J, et al.A pilot study of a wearable apnoea detection device[J]. BMJ Open,2014,4(10) : e005299. https://doi.org/10.1136/bmjopen-2014-005299
  5. Gozani S N. Fixed-site high-frequency transcutaneous electrical nerve stimulation for treatment of chronic low back and lower extremity pain[J]. Journal of Pain Research,2016,9(3):469-479. https://doi.org/10.2147/JPR.S111035
  6. Russell S J, El-Khatib F H, Sinha M, et al. Outpatient glycemic control with a bionic pancreas in type 1diabetes[J]. New England Journal of Medicine, 2014,371(4):313-325. https://doi.org/10.1056/nejmoa1314474
  7. Valentina K, Bianco N, Szymkiewicz S, et al. First clinical experience with the wearable cardioverter defibrillator in left ventricular assist device patients[J]. Europace,2016,18(1):128.
  8. Ridler C. Stroke: Wearable robot aids walking after stroke[J]. Nature Reviews Neurology,2017,13(10):576-577.
  9. Paul G, Irvine J. Privacy implications of wearable health devices[C]//International Conference on Security of Information and Networks. Glasgow, Scotland,UK,2014. ACM,2014:117.