AI-Powered Platform: Microbiome-driven cardiovascular Diagnostics Patch Integration

Over the past few months, I’ve been deeply immersed in developing an innovative approach to early cardiovascular disease detection, a project that merges AI technology, microbiome science, and wearable biosensors.

Our paper, “Microbiome-Driven Cardiovascular Diagnostics via Smart Microneedle Patch Integration,” explores how a microneedle patch paired with an AI-powered platform can detect early signs of heart disease by analyzing real-time blood antigens and health data.

I served as first author, working closely on the model architecture, literature review, and integration of AI-driven analytics. My focus was on ensuring that the prototype not only functioned accurately on synthetic data but also had the potential for real-world scalability, especially in underserved communities where access to advanced diagnostics is limited.

We did something special:

• We went beyond traditional diagnostics that focus solely on cholesterol and heart rate.

• We created a wearable, noninvasive biosensor capable of collecting data painlessly.

• We integrated machine learning algorithms to provide instant, actionable health insights.

Moreover, we created a prototype as a team of 4

We were able to present this at UC Berkeley to professors, specialists, students, alumni, and more.

Read more about the paper here on a published peer-review journal: https://www.ijsr.net/getabstract.php?paperid=SR25613121509