InterSystems IntegratedML-Height and weight prediction

With the improvement of living standards, people pay more and more attention to physical health. And the healthy development of children has become more and more a topic of concern for parents. The child's physical development can be reflected from the child's height and weight. Therefore, it is of great significance to predict the height and weight in a timely manner. Pay attention to the child's developmental state through scientific prediction and comparison.

The project uses InterSystems IRIS Cloud SQL to support by entering a large number of weight and height related data, and establishes AutoML based on IntegratedML for predictive analysis. According to the input parent height, it can quickly predict the future height of children, and judge whether the child's body mass index is based on the current height and weight status. In the normal range.

Key Applications: InterSystems IRIS Cloud SQL, IntegratedML

Function：

By applying this program, the height of children in normal developmental state can be quickly predicted. Through the results, parents can judge whether the child's development is normal and whether clinical intervention is required, which will help to understand the child's future height; through the current weight status Determine whether the current child's BMI is normal and understand the child's current health status.

Application Scenario

1. Children's height prediction

2. Monitoring of child development

Application Principles

The client and server of the application were completed using Vue and Java respectively, while the database was completed using InterSystems Cloud SQL, a cloud database platform from Intersystems.

***The main prediction function of the application uses the Integrated ML of InterSystems Cloud SQL. It effectively helped me quickly create and train data models, and successfully implemented prediction functions.

Test Flow

① Select the module

② Fill in the relevant data. If there is adult sibling data, you can click add to fill in the information.

③ Click Submit and wait for the prediction result to appear in a while.