[dataviz1000]

I'm working on building an AI agent that creates queries over a time-series database focused on financial data. For example, it can quantify Federal Reserve reports and generate a table showing how SPY reacted 30 minutes after, at EoD, at the next day’s open, and at the next day’s EoD. It will plan the database query and then query the data from a materialized view. It is magic!

How would biomedical researchers use tons of time-series data? A better question is: what questions are biomedical researchers asking with time-series data? I'm a lot more interested in generalized querying over time-series data than just financial data. What would be a great proof of concept?

[amber_raza]

That sounds like a fascinating project.

To answer your question: In the biomedical world, the 'Time-Series' equivalent is Patient Telemetry (Continuous Glucose Monitors, ICU Vitals, Wearables).

The Question Researchers Ask: 'Can we predict sepsis/stroke 4 hours before it happens based on the velocity of change in Heart Rate + BP?'

Right now, Evidex is focused on the Unstructured Text (Literature/Guidelines) rather than the structured time-series data, but the 'Holy Grail' of medical AI is eventually combining them: Using the Literature to interpret the Live Vitals in real-time.