Main Reference PaperNovel Approach to Predict Hospital Readmissions Using Feature Selection from Unstructured Data with Class Imbalance, Big Data Research, 2018 [Python]
  • The Hospital Readmission prediction model is investigated from unstructured data. A novel approach is proposed for feature selection and domain related stop words removal from unstructured with class imbalance in discharge summary notes. It uses these features along with other relevant structured data to five iterations of predictions were performed to tune and improve the models.

Description
  • The Hospital Readmission prediction model is investigated from unstructured data. A novel approach is proposed for feature selection and domain related stop words removal from unstructured with class imbalance in discharge summary notes. It uses these features along with other relevant structured data to five iterations of predictions were performed to tune and improve the models.

  • To remove the noisy data from unstructured data.

  • To improve the prediction accuracy.

Aim & Objectives
  • To remove the noisy data from unstructured data.

  • To improve the prediction accuracy.

  • Quality of data in discharge summary is expected to improve readmission prediction

Contribution
  • Quality of data in discharge summary is expected to improve readmission prediction

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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