The Health Insight and Age Estimation API analyzes input values to classify individuals as 'Adult' or 'Senior' and predicts their approximate age. Utilizing advanced Machine Learning techniques for both classification and regression tasks, this API offers valuable insights into age demographics. For further details about the underlying model, please reach out to us.
EXAMPLE CALL:
/nutrition?RIAGENDR=1&PAQ605=2&BMXBMI=38.9&LBXGLU=89&DIQ010=2&LBXGLT=113&LBXIN=17.47
RES:
{
"Age Prediction": "34.516617",
"Value Prediction": "Adult"
}
curl --location --request GET 'https://zylalabs.com/api/6826/health+insight+and+age+estimation+api/10317/nutrition?DIQ010=Required&LBXGLT=Required&LBXGLU=Required&LBXIN=Required&PAQ605=Required&RIAGENDR=Required&BMXBMI=Required' --header 'Authorization: Bearer YOUR_API_KEY'
{
"BMXBMI": "Respondent's Body Mass Index",
"DIQ010": "If the Respondent is diabetic",
"LBXGLT": "Respondent's Oral Microbiome Tests",
"LBXGLU": "Respondent's Blood Glucose after fasting",
"LBXIN": "Respondent's Blood Insulin Levels",
"PAQ605": "If the respondent engages in moderate or vigorous-intensity sports, fitness, or recreational activities in the typical week (a 1 represents that the respondent takes part in weekly moderate or vigorous-intensity physical activity and a 2 represents that they do not)",
"RIAGENDR": "Respondent's Gender (a 1 represents Male and 2 represents Female)"
}
curl --location --request GET 'https://zylalabs.com/api/6826/health+insight+and+age+estimation+api/10318/listallvars' --header 'Authorization: Bearer YOUR_API_KEY'
{
"API Info:": "This API requests per values provide class result ('Adult' or 'Senior'), and also a value for individual predicted Age. The AI algorithm consists of ML (Machine Learning) techniques either for Classification or Regression tasks. Please contact us for more information about the model. We acknowledge the National Center for Health Statistics (NCHS) at the Centers for Disease Control and Prevention (CDC) for providing this Dataset."
}
curl --location --request GET 'https://zylalabs.com/api/6826/health+insight+and+age+estimation+api/10319/info' --header 'Authorization: Bearer YOUR_API_KEY'
After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Health Insight and Age Estimation API simply include your bearer token in the Authorization header.
| Header | Description |
|---|---|
Authorization
|
Required
Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.
|
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This API requests per values provide the class result ('Adult' or 'Senior'), and also a value for the individual predicted Age. The AI algorithm consists of ML (Machine Learning) techniques, either for Classification or Regression tasks. Please contact us for more information about the model. We acknowledge the National Center for Health Statistics (NCHS) at the Centers for Disease Control and Prevention (CDC) for providing this Dataset
The GET Nutrition endpoint returns an age prediction and a classification result ('Adult' or 'Senior') based on input health metrics. The GET listallvars endpoint provides a list of variables and their descriptions, while the GET info endpoint offers general information about the API's functionality and data sources.
The key fields in the GET Nutrition response include "Age Prediction," which indicates the estimated age, and "Value Prediction," which classifies the individual as either 'Adult' or 'Senior'. The listallvars endpoint returns variable names and descriptions.
The GET Nutrition endpoint accepts parameters such as RIAGENDR (gender), PAQ605 (physical activity level), BMXBMI (Body Mass Index), LBXGLU (blood glucose), DIQ010 (diabetes status), LBXGLT (oral microbiome tests), and LBXIN (blood insulin levels). Users can customize requests by providing specific values for these parameters.
The response data from the GET Nutrition endpoint is structured as a JSON object containing two main fields: "Age Prediction" (a numerical value) and "Value Prediction" (a string indicating 'Adult' or 'Senior'). This format allows for easy parsing and integration into applications.
The data utilized by the Health Insight and Age Estimation API is sourced from the National Center for Health Statistics (NCHS) at the CDC. This ensures that the dataset is reliable and representative of health demographics.
Typical use cases for this API include health assessments, demographic analysis, and personalized health recommendations. Researchers and developers can leverage the age classification and prediction to tailor health interventions or marketing strategies.
Users can utilize the returned data by integrating the age prediction and classification into health applications, enabling targeted health advice or interventions. For example, a fitness app could adjust workout plans based on the predicted age and activity level.
Data accuracy is maintained through the use of advanced Machine Learning techniques for classification and regression tasks. Continuous model training and validation against reliable datasets, such as those from the CDC, help ensure the predictions remain accurate and relevant.
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