Evalute Your Risk Using Machine Learning

Our machine learning models were trained with the latest youth diabetes dataset published by Mount Sinai School of Medicine (2024). It is the most comprehensive dataset available for youth diabetes research. Our machine learning algrithms have been fine tuned to produce very high accuracy results.

* risk prediction based on exising dataset, may have bias, please consult your healthcare provider for accurate diagnosis.

** Our website won't store any of your information, no privacy concerns.

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Group 1 Factors Age:
Gender:
Race:
Family History of Diabetes:

Group 2 Factors weight(lb):
height(inch):
Hypertension:
High Cholesterol:
Physical Activity Per Week (hour):
Screen Time Per Day (hours):

Group 3 Factors Total protein intake in past 24 hours (oz):
Total dairy intake in past 24 hours (cup):
Total whole grain intake in past 24 hours (oz):
Total fruit intake in the past 24 hours (cup):
Total Vegetable Intake in the past 24 hours (cup):

Check the box if you want an advanced machine learning prediction by filling more information below

Group 4 Factors (optional) Health condition:
Food Stamps:
Eggs intake past 24 hours (each):
Poultry intake past 24 hours (oz):
Nuts intake past 24 hours (oz):
Milk intake past 30 days:
Solid fat intake past 24 hours (gram):
Oil intake past 24 hours (gram):
Citrus and melons and berries intake past 24 hours (cup):

Evalute Your Risk Using Machine Learning

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