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7b.041.SBU - Medical Insurance Claim Prediction

Project - Summary

A vital task for an insurance company is to identify appropriate medical plans for its potential buyers or existing members. On one hand, the company needs to keep the price competitive. On the other hand, it must anticipate the gain and loss. In this project, we develop an algorithm that allows insurance companies to recommend the appropriate plans to its buyers. Our algorithm can be used to automate the time consuming process of reviewing and and processing user information. Our algorithm considers user profile and their medical history to provide important information needed for a proper medical plan. The proposed method models each user with their medical history as a time series data. At each time step, the model will forecast the medical problems as well as the suitable medical plan to recommended for each user. Moreover, the methods also has the ability to recommend medical plan for an upcoming member.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Minh Hoai Nguyen PI (631) 632-8460 Stony Brook University
Vinh Tran Student Not Available Not Available Stony Brook University
Eugene Sayan Project Mentor Not Available Not Available Softheon

Project - Deliverables

1 Deploy Smart Building testbed
2 Techniques for fault tolerance
3 Proof-of-concept implementation
4 Submit paper demonstrating results from the approach

Project - Benefits to IAB

  1. Saves communication & computation cost – due to scalable and reliable real-time processing on the edge (instead of cloud)
  2. Improve performance of smart building control management - in terms of availability
  3. Knowledge of what type of fault tolerance strategies work for edge computing

Project - Presentation Video

Project - Documents

projects/year7/7b.041.sbu.1565804886.txt.gz · Last modified: 2019/08/14 12:48 by sally.johnson