Online Disease Identification and Diagnosis and Treatment Based on Machine Learning Technology.

Journal: Journal of healthcare engineering
Published Date:

Abstract

The article uses machine learning algorithms to extract disease symptom keyword vectors. At the same time, we used deep learning technology to design a disease symptom classification model. We apply this model to an online disease consultation recommendation system. The system integrates machine learning algorithms and knowledge graph technology to help patients conduct online consultations. The system analyses the misclassification data of different departments through high-frequency word analysis. The study found that the accuracy rate of our machine learning algorithm model to identify entities in electronic medical records reached 96.29%. This type of model can effectively screen out the most important pathogenic features.

Authors

  • Feng Hao
    School of Computing Science, Newcastle University, Newcastle upon Tyne, UK.
  • Kai Zheng
    University of California, Irvine, Irvine, CA, USA.