Osteoporosis detection using a combination of recursive feature elimination and naive bayes classifier with rule-based chatbot testing

HIGHLIGHTS

• What: RFE works by iteratively removing the least important features according to criteria set by the model, thereby focusing on the most relevant features and significantly improving model predictions , . This study proposed a model for developing a rule-based chatbot for the early detection of osteoporosis, employing RFE for feature selection and the Naïve Bayes Classifier for the learning process compared to other feature selection and machine_learning algorithms. This study demonstrated the feasibility of opportunistic osteoporosis screening through CT image texture analysis. The pandemic was accompanied by an "infodemic" of fake news, and the study aimed . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.