The TeenGrowth
package includes functions for:
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Cleaning and processing growth data.
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Calculating Body Mass Index (BMI) and BMI z-scores (BMIZ).
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Forecasting growth metrics.
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Visualizing growth data and weight restoration plans.
To install the package using the `install_github` function: use the following code:
devtools::install.packages("remotes")
library(remotes)
install_github("embark-lab/embarktools")
install_github("embark-lab/TeenGrowth")
Here is a brief example of how to use the TeenGrowth
package:
# Load the package
library(TeenGrowth)
# Example data
data <- read.csv("path/to/your/data.csv")
# Clean the data
cleaned_data <- clean_raw_data(data)
# Forecast BMI
bmi_forecast <- forecast_bmi(clean_data)
# Plot the results of participant # 1
plot_eBMI(clean_data = cleaned_data, forecast_data = bmi_forecast, px = 1)
For a more detailed outline of how to use the R package, refer to the package vignette.
For clinical application, the TeenGrowth
package includes a Shiny application to provide an interactive interface for data input, model selection, and weight restoration planning.
The Shiny application is structured into several tabs:
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Data Input: Upload your data file (CSV or Excel) or use provided demo data.
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Data Specification: Map your data columns to the required fields.
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Model Selection: Select a model to run on your data and view the predictions.
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Weight Restoration Planning: Plan a weight restoration strategy based on the predictions.
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Background and FAQ: Provides additional information and usage instructions.
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Data Input: Upload your data or select demo data.
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Data Specification: Specify the columns corresponding to required fields.
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Model Selection: Select a model and generate predictions.
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Weight Restoration Planning: Input relevant parameters and visualize the restoration plan.
We welcome contributions from the community. If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request on GitHub.