Detecting cardiovascular risk from medical images that already exist — starting with the millions of DXA scans performed every year where aortic calcification is visible but never reported.
Abdominal aortic calcification is visible on virtually every lateral spine DXA image. It is a validated, independent predictor of cardiovascular events. Yet it is almost never reported.
Manual Kauppila scoring is slow (5–10 min per image), subjective, and outside the workflow of DXA technologists. Radiologists reading bone density don't look for it. The finding exists in the image — no one extracts it.
AAC severity independently predicts myocardial infarction, stroke, and cardiovascular mortality. Studies show AAC scores correlate with coronary artery calcium (CAC) and add prognostic value beyond Framingham risk factors. It's a free look at cardiovascular risk from a scan ordered for something else.
An AI model that automatically detects and quantifies abdominal aortic calcification from lateral spine DXA images — turning every VFA scan into a cardiovascular risk assessment.
We've identified datasets across every CardioScreen modality. Some we can access independently — others require an academic PI with institutional affiliation.
Open-access and credentialed datasets — no PI required.
Institutional access, BioLINCC applications, or IRB approval needed.
Endeavor Health and UChicago are both partners in the Institute for Translational Medicine (ITM), which facilitates cross-institutional data sharing and offers pilot grants up to $40K. An Endeavor-affiliated PI can access internal patient data via Epic Data Warehouse and submit BioLINCC applications for NHLBI studies (MESA, ARIC, WHI, CHS, Framingham) simultaneously.
A point-of-care cardiovascular screening platform with tiered architecture — automated triage at the primary care level.
Non-invasive, fully automated. Any MA or nurse can run it.
Rule-based orchestration (not ML) evaluates Tier 1 results. If cardiovascular risk flags are present, the system recommends Tier 2. Deterministic, auditable, explainable.
Only for flagged patients. 5–7 minutes. No sonographer required.
Each sensor modality runs an independent, validated ML model. No black-box fusion. A rule-based orchestration layer combines outputs into a deterministic risk assessment — auditable, explainable, and aligned with FDA's Predetermined Change Control Plan framework.
Each modality (ECG, PPG, auscultation, ultrasound) has its own trained model with independent validation metrics. No cross-modality dependencies. Each component can pursue regulatory clearance independently.
Decision gating uses deterministic rules, not another ML layer. Clinicians and regulators can trace every decision. Update one modality's model within pre-specified performance bounds.
Sensor hardware is interchangeable. The platform integrates any ECG, PPG, stethoscope, or ultrasound probe that meets spec. No vendor lock-in.
Comprehensive IP coverage across the full system — device architecture, AI methods, screening workflows, clinical applications, and decision-support infrastructure. 152+ claims across 5 technology layers. All provisional applications filed March 2026.
Tiered multi-modal screening system, modular cascading architecture, software-defined orchestration platform, multi-organ POC screening with cross-system triage
DXA body composition & visceral fat, standalone automated AAC-24 scoring with dual-energy tissue discrimination, federated learning, incidental CV risk detection, hierarchical beat-embedding ECG rhythm classification
Spatial alignment guidance (10 methods), Doppler angle correction, B-mode-only stenosis estimation without Doppler via ML segmentation
Population benchmarking, DVT screening via bilateral NIRS, specialist consultation marketplace, self-labeling training data flywheel with device-specific normative tables
Concordance-weighted false positive mitigation — Mahalanobis healthy manifold pre-filtering, sequential Bayesian posterior updating, cross-modality concordance gating. Domain-agnostic: applies to any multi-test screening panel
We have the engineering, the clinical infrastructure, and the IP. We need an academic research partner who can shape the science and bring institutional credibility.
A publishable research project, a clinical tool that changes screening, and a platform with real translational potential.
Moonshot Cardio is in the research and development phase. No products have been cleared or approved by the FDA. Descriptions reflect the intended design and development roadmap. All patent applications are provisional.