We help detect diseases earlier so you can start therapy sooner

Our screening algorithms are designed to detect early signs of disease while minimizing false positives. They are designed and developed the medical device standard and validated for the prospective performance.

Available Today

Estimates the likelihood of amyotrophic lateral sclerosis in individual patients based on a complete history that includes a recent electromyograph
MNd-5 v3.0
93% sensitivity
96% specificity
Canada (Class I MDSW)
United States (CDSS)
Estimates the likelihood of ATTR-CM on Tc-99 m PYP based a recent echocardiogram and electrocardiogram
CA-4F v1.4
78-84% sensitivity
77-88% specificity
Canada (Class I MDSW)
United States (CDSS)
IL-1m AIDs
Estimates the likelihood of Still's disease and other IL-1 mediated autoinflammatory diseases based on a complete clinical history
SD-9 v3.0
100% sensitivity in AOSD
96% sensitivity in all IL-1m AIDs
Canada (Class I MDSW)
United States (CDSS)
Identifies individual patients in which Chapter 13 of the 2020 Diabetes Canada guidelines recommend medical management with a cardiometabolic antidiabetic agent ( SGLT2 inhibitor or GLP-1 RA)
Primary Care, Internal Medicine
CMAA-6 v3.0
Canada (CDSS)
Identifies and characterizes the medical management of patients diagnosed with HoCM with peak LVOT gradient of 50 mmHg or greater and LVEF of 55% or greater.
Internal Medicine, Cardiology
OA007 v1.0
Canada (CDSS)

Our Science

Relevant Parameters

Our algorithms rely exclusively on relevant clinical parameters. We don't employ big data techniques to draw loose inferences from codes or claims or require structured data. Our machine learning tools are embedded in our data extraction platform rather than in our algorithms. They only operate unsupervised at thresholds that yield 100% accuracy. We manage uncertainty with technology-enabled abstraction by trained healthcare professionals.

This allows us to build tools that are unrivalled in their precision. It's why our ATTR-CM algorithm is driven by reported echo parameters like IVSD, E/E' and GLS, why our ALS algorithm can incorporate the presence of sharp waves on EMG in patients with clinical fasciculations and why our IL-1 mediated autoinflammatory diseases algorithm can account for fever periodicity in its calculations.

Explainable Predictions

Our reports clearly and transparently explain why patients may be suitable for follow-up investigations or referrals to specialty centres. The clinical parameters that drove our calculations are always reported alongside pertinent positives, pertinent negatives and other signs or symptoms necessary to complete the clinical picture.

Our mission is to empower physicians with better tools. Our reports reflect our best efforts to realize it.

Data Labs

We deploy our digital diagnostics exclusively at our clinical data labs because:

  • It allows us to control for variability in source data formats;

  • We can achieve greater reliability and accuracy than if we were to deploy our solutions locally; and

  • It makes life easier for our customers.

We go to great lengths to keep health information safe and secure including through the adoption of novel asymmetric de-identification and encryption techniques.

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