Cardiovascular diseases (CVDs) are the leading cause of death globally, taking an estimated 17.9 million lives each year. CVDs are a group of disorders of the heart and blood vessels and include coronary heart disease, cerebrovascular disease, rheumatic heart disease and other conditions.
Almost 86% of diabties patient get cardiovascular diseases.
I have a working prototype inside smart health app that can predict if a patient is in risk of get a cardiovascular disease based on blood pressure, age, gender, fasting glucose level, smoking status and alcohol intake (see the images below from the app).
I have the knowledge to build AI healthcare prediction models and started working on diabetes prediction models based on BMI and fasting glucose measurements.
The current cardvascular diseases model was trained using a 70,000 patient dataset and our model uses Gradient Boosting algorithm that gave an AUC (Area under the curve) of 80%. The prediction is performed on the cloud, we use Flask framework & python language on Heroku servers so please enable internet on your phone before trying the prediction.
The image on the most right shows the result of a prediction.
You need to key-in the following information before pressing predict:
1) Age in years
2) Height in cm
3) Weight in kg
4) Systolic pressure (range from 120 mm Hg to 200 mm Hg)
5) Diastolic pressure (range from 60 mm Hg to 100 mm Hg)
6) Cholesterol level (Normal: Less than 200 mg/dL; Above normal : 200 to 239 mg/dL ; High: 240 mg/dL)
7) Fast glucose level (Normal : 99 mg/dL or lower; Above normal: 100 to 125 mg/dL; High: 126 mg/dL)