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DynaHealth Backend (Data Collection, Processing, Training, and Deployment)

Authors: Duy Ho, Hieu Trinh, Nhung Tran

Award: 1st place

Award Page: https://info.umkc.edu/hack-a-roo/spring-2021-it-track/

Note: For frond-end, please visit: https://github.com/ngchieu857529/hackaroo_spring_2021

Motivation

Health insurance is one of the most important protections for an individual. Having a health insurance plan not only helps ease the mind but also covers a significant amount of cost in critical or unexpected conditions such as illness and accident. However, not everyone has easy access to and knowledge about health insurance in a convenient and informative way. Thus, users may not have sufficient awareness about the topic to make a decision. Moreover, data from many sources are not represented in a transparent or meaningful manner, leading to uncertainty and confusion.

Overview

image

Main Features

Two domains:

COVID-19:

Statistics

  • Number of cases
  • National
  • Statewide
  • County

Distribution of Cases

  • Geography

Vaccination

  • Total first/second doses
  • Geographic Distribution of doses

Health Insurance

Socioeconomic Visualizations:

  • Employment status
  • Insurance status
  • Geography
  • Coverage type
  • Family status
  • Education
  • Income
  • Poverty

Smart Insurance:

  • Cost Estimator
    • Chatbot
    • Plan Recommendations
  • Neural Network

Implementation

image

Front End

  • React:
    • Leading platform for quick, reliable, and scalable web applications.
    • Mobile-friendly
    • Maintainability and support
  • Vercel: deployment platform. Integrated with GitHub with automatic deployment

Backend

  • Python: best framework for data science and deep learning
  • PyTorch: one of the most popular frameworks for building DL models
  • Jupyter Notebook: an interactive tool to work and share Python code efficiently
  • Jupyter Dash + Plotly: powerful & interactive visualization tool for Python

Datasets

image

Approach

  • Data Research/Collection

  • Data Curation

    • Data simplification
    • Eliminate invalid values
  • Data Integration

    • Time-series Analysis
    • Boundary Integration
  • Data Visualization

  • Multiple charts/graphs

  • Model Training

    • Data Normalization
    • Neural Network architecture: 9 layers
  • Model Inference

    • Input: Age, BMI, Sex, Children, Smoke, Location
    • Output: estimated yearly
  • Model Deployment

    • API endpoints: hackaroo.ngrok.io/api/model/quick
    • Parameters: age, height, weight, children, smoker, state
    • https://hackaroo.ngrok.io/api/model/quick?height=150&weight=55&age=65&children=1&smoker=0&sex=1&state=MO [Deprecated]
  • Application Deployment

    • Vercel: https://hackaroo-spring-2021.vercel.app/ [Deprecated]
    • Automatic deployment upon commit.

Sample Server JSON

Input : http://hackaroo.ngrok.io/api/model/quick?height=150&weight=55&age=65&children=1&smoker=0&sex=1&state=MO Output:

{
  "plans": {
    "silver": {
      "4748A0001A002008": {
        "State Code": "MO",
        "region": "southeast",
        "Metal Level": "silver",
        "Issuer Name": "WellFirst Health",
        "Plan ID (Standard Component)": "4748A0001A002008",
        "Plan Marketing Name": "WellFirst Silver HSA-E 4500X",
        "Plan Type": "EPO",
        "Customer Service Phone Number Local": "1-866-514-4194",
        "Customer Service Phone Number Toll Free": "1-866-514-4194",
        "Customer Service Phone Number TTY": "1-866-514-4194",
        "Network URL": "http://www.wellfirstbenefits.com/find-a-doc/marketplace-epo-plan-providers/",
        "Plan Brochure URL": "http://www.wellfirstbenefits.com/Individuals-and-Families",
        "Summary of Benefits URL": "https://sbc.wellfirstbenefits.com/api/GetPdf?wellFirst_WellFirst%20MO%20Silver%20HSA-E%204500X01_0121.PDF&true",
        "Individual+1 child, Age 50+": "888.99"
      },
      "99723M0009011": {
        "State Code": "MO",
        "region": "southeast",
        "Metal Level": "silver",
        "Issuer Name": "Ambetter from Home State Health",
        "Plan ID (Standard Component)": "99723M0009011",
        "Plan Marketing Name": "Ambetter Balanced Care 11 (2021)",
        "Plan Type": "EPO",
        "Customer Service Phone Number Local": "1-855-650-3789",
        "Customer Service Phone Number Toll Free": "1-855-650-3789",
        "Customer Service Phone Number TTY": "N/A",
        "Network URL": "https://ambetter.homestatehealth.com/findadoc",
        "Plan Brochure URL": "https://www.ambetterhealth.com/content/dam/centene/ambetter/brochures/MO-2021.pdf",
        "Summary of Benefits URL": "https://api.centene.com/SBC/2021/99723M0009011-01.pdf",
        "Individual+1 child, Age 50+": "901.26"
      },
      {...},
       ...
    }
  }
}

Embedded Interactive Visualizations

Media Media2 Media3 Media4 Media5 Media6 Media7 Media8 Media9 Media10 Media11 Media12 Media13

Future Scope

  • Human in the loop: Real-time feedback​
  • Multiple simultaneous messages from each side.​
  • More knowledge domains​
  • UI improvement​
  • Model deployment on the Cloud (Amazon AWS, Microsoft Azure, …)​
  • Application Deployment in Google Playstore​ and App Store
  • Multi-modality Analysis
  • Natural Language Processing​
  • Object Detection (to interpret user’s uploaded images)​
  • User Sentiment Analysis​
  • Diverse text-to-speech models (gender-based, age-sensitive, and more natural-sounding)​
  • Speech-to-text features (to simulate phone calls or Facetiming)​

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