MedTWIN.AI
Research stage

CardioGuard

Post-MI cardiac risk forecasting designed to be explainable, testable, and clinically reviewable.

Overview

Secondary prevention, with governance

CardioGuard is a research-stage tool for forecasting cardiac risk from multi-source signals. The design prioritizes interpretability, conservative alerting, and traceable inputs.

Multi-source wearable + clinical signals
Conservative alert thresholds
Explainability-first outputs
Audit trail for decisions
CardioGuard

Built for secondary prevention

Safety-first outputs tied to traceable inputs, not opaque models.

Multi-source signals

Wearables, CGM, and cohort data with provenance.

Risk stratification

Forecast risk and surface likely drivers.

Continuous monitoring

Safety-first alerts with interpretability.

Audit-ready

Traceable inputs and deterministic rules.

Clinical workflow

01

Data ingestion

Collect wearable and clinical signals

02

Risk modeling

Multi-factor cardiac risk assessment

03

Alerting

Conservative, interpretable warnings

04

Review

Clinician validation with full audit trail

Join a CardioGuard pilot

If you’re running a cohort study or monitoring workflow, we’d love to partner on validation.