A data science project which focuses on finding if any patient has a risk of getting heart disease according to the user's medical data inputted into the system. Prediction is carried out according to values from 14 parameters and the model is trained with 5000 data to receive a highly accurate result. The project includes a web application and a mobile application targetting the end-users and an IoT device was built to get the ECG in real-time.

• Predict heart diseases (85% Accuracy)
• Track real-time ECG of the patient (IoT device to track ECG and real-time ECG variation is shown from the application)
• View history of the patient's medical records
• Easy to track medical records
• Register new patients to the system
• Update patient data

• Python for ML component development
• Naive Bayes as the main classifier
• Angular
• Node.js
• MySQL
• Android Development Java
• Android Studio
• Arduino

👤 Athindu Umayanga

• Github: @Athindu

👤 Avishka Pasindu

• Github: @Avishka

👤 Bavindhu Amarathunga

• Github: @Bavindhu

👤 Hashan Senevirathne

• Github: @Hashan

👤 Anuja Kaushala

• Github: @Anuja

👤 Ridma Samarawikrama

• Github: @Ridma