Predict Disease Onset Years Before Diagnosis

A patent-pending AI algorithm that identifies patients at risk for Parkinson’s, autoimmune disorders, and other critical conditions — using data that already exists in your systems.

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By the time most neurodegenerative and autoimmune conditions are clinically diagnosed, the disease has been progressing for years. Early intervention dramatically improves outcomes, but traditional screening methods are expensive, invasive, and catch only a fraction of at-risk patients.

FyndEm Clinical takes a different approach. Our patent-pending algorithm analyzes patterns in existing patient data — lab results, prescription history, visit patterns, comorbidities — to identify patients whose profiles match the pre-diagnostic signatures of specific diseases.

What FyndEm Clinical Delivers

Early Disease Risk Scoring

Every patient receives a risk score for targeted conditions based on their complete data profile. High-risk patients are flagged for clinical review, enabling intervention years earlier than traditional diagnosis pathways.

Pattern-Based Detection

Our AI identifies subtle combinations of signals that individually appear unremarkable but together form a pre-diagnostic signature. The algorithm learns from confirmed outcomes and continuously improves its accuracy.

Clinical Trial Patient Identification

For research hospitals and pharmaceutical partners, FyndEm Clinical identifies patients who match specific trial eligibility criteria — accelerating enrollment and reducing the cost of patient recruitment.

Population Health Insights

Aggregate risk scoring across patient populations reveals disease burden patterns, geographic concentrations, and emerging trends that inform resource allocation and preventive care programs.

● Patent-Pending Technology