New Clinical Outcomes at ISC 2026 Demonstrate Aidoc’s Superior AI-Powered Triage of Large and Medium Vessel Occlusions

Establishing a new benchmark for stroke triage, comparative research reveals critical performance gaps and validates Aidoc’s platform as the superior choice

NEW ORLEANS, Feb. 4, 2026 /PRNewswire/ — Aidoc, the leading clinical AI platform, today announced the presentation of two new scientific abstracts comparing AI-powered stroke solutions at the International Stroke Conference (ISC) 2026. The data, presented by independent academic institutions, highlights the real-world reliability of Aidoc’s neuro AI algorithms and demonstrates a significant performance advantage over other market solutions, particularly in the triage of medium vessel occlusions (MeVOs).

As health systems increasingly rely on AI to expedite time-sensitive critical cases, these invaluable tools demand rigorous performance evaluation. These new findings presented at ISC highlight significant clinical value gaps between available AI solutions, specifically regarding sensitivity and the device’s anatomical coverage.

A comparative study conducted by The University of Texas Medical Branch evaluated the performance of Aidoc against a conventional AI vendor in a clinical setting.¹ The study compared the triage accuracy of both systems across 1,557 consecutive CTA exams.

The results revealed a distinct performance gap, particularly in the flagging of MeVOs, which are often more difficult to identify but critical for patient outcomes:

• Higher Large Vessel Occlusion (LVO) Sensitivity: For head-to-head LVOs (ICA or proximal MCA-M1), Aidoc demonstrated 92.6% sensitivity, outperforming the conventional solution’s 70.4%.
• Superior MeVO Sensitivity: With Aidoc FDA cleared for analysis in more total segments, the device achieved a 92.3% sensitivity for flagging MeVO segment occlusions, compared to just 17.3% for the conventional AI solution — a disparity of over 75%.
• Overall Reliability: Aidoc achieved a negative predictive value (NPV) of 99.3%, providing clinicians with high confidence in the notifications the solution provides.

In a separate study presented by Saint Louis University School of Medicine, researchers analyzed 1,000 CTA exams to evaluate the effectiveness of Aidoc’s VO algorithm in a “messy” real-world environment.² The study demonstrated that high fidelity performance supports AI integration into workflows for evaluating both anterior and posterior circulation occlusions.

• High Specificity: The solution maintained a 97.1% specificity, minimizing false positives.
• Broad Vessel Coverage: The algorithm successfully flagged occlusions in both the anterior circulation (87.6% sensitivity) and the more challenging posterior circulation (79.2% sensitivity).

“These findings illuminate a crucial distinction in the market: simply having an algorithm isn’t the same as delivering clinical-grade performance,” said Elad Walach, co-founder and CEO of Aidoc. “When we see a 75% gap in sensitivity for identifying MeVOs, it underscores that high-fidelity AI is a necessity for ensuring that the complete spectrum of complex, time-sensitive cases are flagged for immediate review.”

Aidoc will be at Booth #601 throughout ISC 2026 showcasing its Full Brain AI Solution.

About Aidoc 
Aidoc is a global leader in clinical AI, with the most FDA-cleared computer-aided detection (CAD) solutions in the market. Aidoc powers clinical decision-making for more than 60 million patients each year, delivering real-time AI that eases cognitive load, improves productivity and supports better care across imaging and clinical data.

Built on its proprietary AI Operating System (aiOS™), Aidoc integrates directly into provider workflows at the point of care, helping clinicians prioritize cases more efficiently and make informed decisions with confidence. With adoption across more than 1,600 medical centers worldwide, Aidoc supports health systems as they scale clinical AI responsibly and effectively.

Media Contact 
press@aidoc.com
US:+1 929 255 1449 

Citations

1. Al Taweel A. MD, Al Jadiry H. MD, McCaffrey P. MD, Walser E. MD. “Comparative Evaluation of Two Commercial AI Solutions for Vessel Occlusion Detection in a Real-World Clinical Setting.” The University of Texas Medical Branch, TX, USA.
2. Vermette N., Kleinschmidt K., Barkhordar A., Fox J. D., Sudanagunta K. MD. “Impact of an AI-Based Vessel Occlusion DetectionAlgorithm on Occlusion Identification in a Real-World Stroke Workflow.” Department of Radiology, Saint Louis University School of Medicine, St. Louis, MO, USA.

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