Revolutionize Your Apps with Azure Machine Learning & OpenAI

Table of Contents

1. Introduction
2. Features
3. Solution Components
4. Setting up PowerApps
5. Data Sources
6. Screens and User Interface
7. Predicting Health Expenses
8. Integrating Open AI
9. Using AI Builder for Prescription Processing
10. Conclusion

Integrating Power Apps with Azure Machine Learning and Open AI

In this article, we will explore the process of integrating Power Apps with Azure Machine Learning and Open AI to Create a health expense tracking app. The app utilizes a machine learning model to predict health expenses Based on various parameters and provides personalized plans to save funds. We will discuss the features of the app, the solution components involved, and the step-by-step process of setting up Power Apps and integrating it with Azure Machine Learning and Open AI.

1. Introduction

The health expense tracking app is a powerful tool designed to help individuals keep track of their health expenses and save money. By utilizing Azure Machine Learning and Open AI, the app predicts health expenses based on parameters like age, sex, BMI, number of children, and smoking habits. The app then generates a detailed personalized plan to save for these expenses, providing users with an effective strategy to manage their healthcare costs.

2. Features

The health expense tracking app offers several features to help users effectively manage their health expenses:

• Prediction of Health Expenses: The app uses a custom-built SQL automl model integrated with Power Apps to predict health expenses based on user inputs.
• Personalized Savings Plan: Based on the predicted expenses, the app generates a customized plan to save funds for healthcare costs.
• Integration with Open AI: The app utilizes Open AI's API to create the personalized savings plan, providing users with actionable steps to save money.
• User-Friendly Interface: The app's interface is designed to be simple and easy to use, allowing users to input their parameters and view the predicted expenses and savings plan effortlessly.

3. Solution Components

The health expense tracking app comprises three main components:

1. Canvas App: This is the interface of the app where users input their parameters and view the predicted expenses and savings plan.
2. Power Automate Flow: This flow links the canvas app to the Azure automl model. When the user interacts with the app, the power automate flow sends an HTTP request to the automl endpoint and retrieves the prediction results.
3. Azure automl Model: It is the machine learning model that predicts health expenses based on the input parameters. The deployed endpoint returns a float number representing the expenses in USD.

4. Setting up Power Apps

To set up Power Apps for the health expense tracking app, the following steps are required:

1. Obtain an API key from Open AI.
2. Create an account for Power Apps and Power Automate.
3. Ensure an active Azure account and deploy an Azure automl model to get an endpoint for predictions.

5. Data Sources

The Power App includes the Open AI connector, which allows users to add the connector to the app and use it to extract data. It also includes the Power Automate flow, which is triggered when a button is pressed in the app. The flow sends an HTTP request to the model endpoint and passes the JSON response back to the Power App for utilization.

6. Screens and User Interface

The health expense tracking app's interface consists of input fields for parameters like age, sex, BMI, number of children, and smoking habits. Once these parameters are provided, the app predicts the expenses using the machine learning model. The app then generates a personalized savings plan based on the inputs and the model's results.

7. Predicting Health Expenses

In this step, users input their parameters into the app's interface, and the app utilizes the integrated Azure automl model to predict their health expenses. The predicted expenses are displayed to the user, providing them with an estimation of their healthcare costs.

8. Integrating Open AI

To create the personalized savings plan, the app integrates Open AI's API. The app utilizes the correct model from Open AI and provides a prompt that includes the user's input parameters. Using various techniques of prompt engineering, the app ensures accurate and human-like responses from the Open AI model, offering users actionable steps to save for their health expenses.

9. Using AI Builder for Prescription Processing

The health expense tracking app leverages Power Apps' AI Builder feature to process prescriptions. The AI Builder allows the app to add an AI model without the need for a connector or separate flow. By using the pre-built model "Extract All Text," the app can analyze and extract text from prescriptions, making it easier to Read and understand the details.

10. Conclusion

Integrating Power Apps with Azure Machine Learning and Open AI offers a powerful solution for tracking health expenses and saving money. By utilizing predictive models and AI capabilities, users can accurately estimate their healthcare costs and receive personalized plans to manage and save for their health expenses efficiently. The seamless integration of Power Apps with Azure Machine Learning and Open AI provides a user-friendly and effective solution for healthcare cost management.

Highlights:

• The health expense tracking app utilizes Azure Machine Learning and Open AI to predict health expenses and generate personalized savings plans.
• Users can input parameters like age, sex, BMI, number of children, and smoking habits to estimate their healthcare costs.
• Open AI's API is integrated to create personalized savings plans, providing actionable steps for cost-saving.
• The app's interface is user-friendly and allows for simple input of parameters and visualization of predicted expenses.
• Power Apps' AI Builder feature can be used for prescription processing, enabling easy extraction of information from prescriptions.

FAQ

Q: How does the health expense tracking app predict health expenses? A: The app utilizes a machine learning model integrated with Power Apps to predict health expenses based on parameters like age, sex, BMI, number of children, and smoking habits.

Q: Can the health expense tracking app create personalized savings plans? A: Yes, once the expenses are predicted, the app generates a customized plan to save funds for healthcare costs based on the user's inputs and the results of the machine learning model.

Q: Does the app support integration with Open AI? A: Yes, the app utilizes Open AI's API to create personalized savings plans, providing users with actionable steps to save money based on their predicted expenses.

Q: How user-friendly is the app's interface? A: The app's interface is designed to be simple and easy to use. Users can input their parameters and view the predicted expenses and savings plan effortlessly.

Q: Can the app process prescriptions? A: Yes, the app leverages Power Apps' AI Builder feature to process prescriptions. The integrated AI model can extract text from prescriptions, making it easier to read and understand the details.

Q: What are the advantages of integrating Power Apps with Azure Machine Learning and Open AI? A: The integration allows for accurate prediction of health expenses, personalized savings plans, and easy management of healthcare costs. Users can make informed decisions and take actionable steps to save money.