Main Reference PaperOptimizing Outpatient Appointment System using Machine Learning Algorithms and Scheduling Rules: A Prescriptive Analytics Framework, Expert Systems With Applications, 2018 [Java/Python/R]
  • The framework of prescriptive analytics intends to exploit the information related to the patients from different sources to discover the risk and classify of patients on the basis of no-show through the machine learning technique.

+ Description
  • The framework of prescriptive analytics intends to exploit the information related to the patients from different sources to discover the risk and classify of patients on the basis of no-show through the machine learning technique.

  • To manage the patient no-shows in the clinical

  • To enhance the appointment system performance

+ Aim & Objectives
  • To manage the patient no-shows in the clinical

  • To enhance the appointment system performance

  • To develop the system using the machine learning techniques along with the optimization improves the accuracy of prediction.

+ Contribution
  • To develop the system using the machine learning techniques along with the optimization improves the accuracy of prediction.

  • Operating system: Ubuntu / Windows

  • Java/Python/R

+ Software Tools & Technologies
  • Operating system: Ubuntu / Windows

  • Java/Python/R

  • 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.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.

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