engineering the heartbeat of tomorrow
cardeon Labs
cardeon labs
About us
Cardeon Labs is an independent, student-led biotech micro-startup exploring the intersection of cardiology and artificial intelligence. Our current focus is developing AI-driven models and wearable systems for early prediction of arterial plaque rupture and cardiovascular risk.
We were founded in 2025 by Athira Gopan, a student researcher from Bangalore, India, focused on addressing cardiovascular health disparities through AI and wearable technology.
research and innovations
projects
Each project at Cardeon Labs merges AI, biomedical science, and design to advance early cardiac diagnostics.
1
Plaque Rupture Prediction Model v1.0
This project explores how deep learning can identify early signs of plaque instability using intravascular imaging. The CNN model classifies arterial cross-sections as rupture-prone or stable, laying the foundation for predictive cardiology diagnostics. Enables proactive identification of high-risk patients, contributing to early intervention and reduced cardiovascular mortality.Methods & Tools:
Python, TensorFlow, Keras, MatplotlibStatus: Prototype (v1.0 in development)
AI-Driven Wearable for Plaque Instability Detection
This concept proposes an AI-integrated smartwatch capable of detecting micro-signals indicating arterial instability using PPG and vibration sensors. Aims to bridge wearable technology and preemptive healthcare, reducing the global burden of sudden cardiac events.Goal:
To create an accessible, continuous monitoring system for individuals at cardiac risk.Status: Provisional patent draft complete
CardioYouth-India Dataset
An open-source dataset mapping cardiovascular risk factors in young Indian populations, focusing on lifestyle, diet, and hereditary indicators.Goal:
To provide region-specific data that improves accuracy of AI training models.Impact:Supports localized predictive analytics and equitable global heart health research.Status: Preparing for Zenodo release
AI in Plaque Rupture Prediction: Research Paper
A detailed review and meta-analysis of existing AI models used in plaque rupture prediction, highlighting challenges, limitations, and ethical considerations.Goal:
To identify gaps in current literature and outline future directions for AI-based cardiovascular diagnostics.Impact:Bridges academic understanding with real-world AI applications in preventive cardiology.Status: Published on Research Archive of Rising Scholars
