Predictive Analytics: Bayesian Heart Score Model
EzBeat has trained a sophisticated Bayesian model to predict individual heart scores. This model analyzes various health parameters over time to provide personalized insights into heart health trends. The parameters considered are:
- Date
- Steps per day
- Sleep (hrs)
- Resting Heart Rate
- Systolic blood pressure
- Diastolic blood pressure
- Weight
- Alcohol consumption (# of drinks)
- Smoking (# of cigarettes)
- Vaping (Y/N)
- HRV


Cohort-Based Gamified Analysis
We trained our Bayesian model on a cohort of 4 participants and turned the results into a fun, gamified leaderboard! Compete, improve, and earn your badge!
🎯 Gamified Leaderboard (Top Performers)
🏅 Elite: Points > 20 | 🥈 Advanced: Points > 10 | 🔰 Beginner: Points ≤ 10
The leaderboard motivates participants to improve their heart scores and earn higher badges. Who will be the next Elite performer?
Experiments Lab
Ask us whatever questions you would want EZBEAT to answer. Your questions will go towards our research and training, to improve our services.
Participate in Our Research
Help us advance heart health science by participating in our clinical trials and research studies. Your involvement could help shape the future of heart health monitoring.
Join a Study