Detection of Dengue Fever by Using K-Means Clustering With Svm Classifier

@article{1702265,
      author = {Ardhala Prabhavathi, Bommareddy Chandra Lekha, Aamani Narra, Adapa Navya Santoshi},
      title = {Detection of Dengue Fever by Using K-Means Clustering With  Svm Classifier},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {11},
      pages = {17-20},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702265.pdf},
      abstract = {Dengue is a major health problem in tropical and Asia-Pacific regions. Dengue is a mosquito-borne infection that can lead to a severe flu-like illness. It is caused by four different viruses and spread by Aides mosquitoes. According to World Health Organization (WHO) every year nearly 400 million people are affected by Dengue Fever. This project uses blood smear images with white blood cells classification. Here based on White Blood Cells (WBC) classification it is going to detect whether a person is infected with dengue or not. The proposed method is implemented with the help of K-Means clustering with Support Vector Machine (SVM) classifier. The proposed K-Means clustering with SVM classifier gives better results.},
      keywords = {blood smear images, K-Means clustering, SVM classifier.},
      month = {May},
  }