📦 Un Design System pour l’Assurance Maladie
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Updated
Feb 4, 2025 - Vue
📦 Un Design System pour l’Assurance Maladie
Predicting health insurance cost from Morality data using Machine Learning techniques
An AI, Machine Learning and Blockchain based healthcare ecosystem that predicts health outcome, divulges users' and environmental health risk; mitigates illicit drug use.
This project explains on how to build a machine learning algorithm for calculating the medical insurance costs. Check out my video on this topic for the complete video explanation.
Golang X12 parser, validator and transformer
Analysis of the effect of different types of financial products on financial wellbeing.
A small notebook to walk through if shared or individual plans are a better choice
Predictive Data Mining for Health Insurance data
This project helps the community to set their health as the first preference over wasting a lot of time on analyzing the health insurance premiums.
Health insurance marketplace data used in April 2017 story
This Python collection provides come samples of developed systems in the Python programming language.
The "US Medical Insurance Costs" project explores and analyzes a dataset containing medical insurance costs for patients in the United States. The project was completed as part of the Codecademy Data Science Career Path.
Natural Language Processing Based RealTime Voicemail Routing System for Health Insurance Enterprise
What accounts for the wide gap in health insurance rates between rural and urban counties?
Health Insurance Coverage Rules Interepretation Corpus
By Constructing a regression model without interactions for data obtained from a health insurance company- information from its subscribers who had made claims resulting from ischemic (coronary) heart disease- we are able to predict the total costs of services provided. This project helps interpret the data through appropriate scatter plots (suc…
U.S. Health Insurance Appeal Overturn Prediction App
An insurance company wants to start selling vehicle insurance to the customers that already have health insurance. They believe that one of the ways to reach as many customers as possible with the least amount of calls is to make a machine learning model that sorts the list of customers to maximize the amount of contracted services.
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