Brainomix 360

Clinical Evidence

Explore 60+ peer-reviewed studies validating Brainomix 360 performance and value, published by international academic groups. Brainomix products have been rigorously tested across diverse clinical settings—find the evidence here.

Clinical Evidence

Changes in collateral status during transfer for thrombectomy are predictive of functional outcome in large vessel occlusion stroke

Visual versus automated collateral scoring on CT angiography for predicting outcome after endovascular therapy for large-vessel occlusion stroke: a prospective multicentre study

One scan, two answers: RAPID vs Brainomix agreement in thrombectomy patients

Neuroimaging of acute myocardial injury in stroke: insights into brain lesion locations and network disconnections

Artificial intelligence-based software to support mechanical thrombectomy transfer decision in low-volume primary stroke centers: a multicenter, retrospective study

Transcranial direct current stimulation is safe and feasible in hyperacute ischemic stroke (DICAST-SF trial)

Artificial intelligence imaging decision support for acute stroke treatment in England: a prospective observational study

Artificial Intelligence–Driven Detection of Large Vessel Occlusions on NCCT: A Multi-Institutional Study

Automated Vessel Occlusion Software in Acute Ischemic Stroke: Pearls and Pitfalls

Prospective Evaluation of Artificial Intelligence Imaging Support Software for Acute Ischemic Stroke in the Mayo Clinic Telestroke Network

Phase 2 study design and analysis approach for BBT-877: an autotaxin inhibitor targeting idiopathic pulmonary fibrosis

Automatically Quantified Follow-Up Imaging Biomarkers Predict Clinical Outcomes After Acute Ischemic Stroke

Artificial Intelligence assisted detection of large vessel occlusion on CT angiography in acute stroke patients: A multi-reader multi-case study

Automated assessment of collateral circulation and infarct core: predictors of functional outcomes in acute ischemic stroke following endovascular thrombectomy

CT perfusion for lesion-symptom mapping in large vessel occlusion ischemic stroke

The e-STROKE Study: The Design of a Prospective Observational Multicentral Study

Health Innovation Oxford and Thames Valley (previously Oxford AHSN) Final evaluation report of e-Stroke (as part of the AI in Health and Care Award)

Revolutionizing Acute Stroke Care: A Review of Food and Drug Administration-Approved Software as Medical Devices for Stroke Triage

Current Stroke Solutions Using Artificial Intelligence: A Review of the Literature

Thrombectomy for Stroke With Large Infarct on Noncontrast CT (TESLA randomised clinical trial)

The Absence of Typical Stroke Symptoms and Risk Factors Represents the Greatest Risk of an Incorrect Diagnosis in Stroke Patients

Current Applications and Future Perspectives of Artificial and Biomimetic Intelligence in Vascular Surgery and Peripheral Artery Disease

Adoption, orchestration, and deployment of artificial intelligence within the National Health Service—facilitators and barriers: an expert roundtable discussion

Patients Randomised to Glenzocimab Suffered Less Haemorrhagic Transformation at 24 Hours Compared to Placebo: AI-Imaging Sub-Analysis of the ACTIMIS Trial

Artificial intelligence-based decision support software to improve the efficacy of acute stroke pathway in the NHS: an observational study

Automated Assessment of the DWI-FLAIR Mismatch in Patients with Acute Ischemic Stroke: Added Value to Routine Clinical Practice

Clinical value of automated volumetric quantification of early ischemic tissue changes on non-contrast CT

Real-world evaluation of Brainomix 360 software

Automated assessment of ischemic core on noncontrast computed tomography: a multicenter comparative analysis with CT perfusion

Comparison of CT Perfusion Software Packages for Thrombectomy Eligibility

Impact of e-ASPECTS software on the performance of physicians compared to a consensus ground truth: a multi-reader, multi-case study

Hyperdense Artery Sign in Patients With Acute Ischemic Stroke–Automated Detection With Artificial Intelligence-Driven Software

Falsely Normal CT Perfusion Ischemic Core Readings Are Common and Often Associated with Deep Infarcts

Automated CT angiography collateral scoring in anterior large vessel occlusion stroke: A multireader study

Diagnostic accuracy of decision-support software for the detection of intracranial large-vessel occlusion in CT angiography

Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy patients

Automated evaluation of ASPECTS from brain computerized tomography of patients with acute ischemic stroke

External Validation of e-ASPECTS Software for Interpreting Brain CT in Stroke

Comparison of automated ASPECTS, large vessel occlusion detection and CTP analysis provided by Brainomix and RapidAI in patients with suspected ischaemic stroke

Automated scoring of collaterals, blood pressure, and clinical outcome after endovascular treatment in patients with acute ischemic stroke and large-vessel occlusion

Interpretable Machine Learning Modeling for Ischemic Stroke Outcome Prediction

e-ASPECTS software improves interobserver agreement and accuracy of interpretation of aspects score

Full Reperfusion Without Functional Independence After Mechanical Thrombectomy in the Anterior Circulation

Clinical Outcomes in Basal Ganglia Strokes Treated With Mechanical Thrombectomy

Improved stroke care in a primary stroke centre using AI-decision support

Evolution of Hypodensity on Non-Contrast CT in Correlation with Collaterals in Anterior Circulation Stroke with Successful Endovascular Reperfusion

Artificial Intelligence software to interpret brain computed tomography in patients with stroke: external validation of e-ASPECTS software for Interpreting Brain CT in Stroke

Automated detection and segmentation of intracranial hemorrhage suspect hyperdensities in non-contrast-enhanced CT scans of acute stroke patients

Novel selection paradigms for endovascular stroke treatment in the extended time window

Artificial Intelligence and Acute Stroke Imaging

Thrombectomy for Stroke in the Public Health Care System of Brazil (RESILIENT)

Detection of ischemic changes on baseline multimodal computed tomography: expert reading vs. Brainomix and RAPID software

Innovative use of artificial intelligence and digital communication in acute stroke pathway in response to COVID-19

Interaction between time, ASPECTS, and clinical mismatch

Thrombolysis in Stroke With Unknown Onset Based on Non-Contrast Computerized Tomography (TRUST CT)

Impact of slice thickness on clinical utility of automated Alberta Stroke Program Early Computed Tomography Scores

Region-specific agreement in ASPECTS estimation between neuroradiologists and e-ASPECTS software

Automated versus manual imaging assessment of early ischemic changes in acute stroke: comparison of two software packages and expert consensus

Automated ASPECTS in Acute Ischemic Stroke: A Comparative Analysis with CT Perfusion

e-ASPECTS derived acute ischemic volumes on non-contrast-enhanced computed tomography images

Electronic Alberta Stroke Program Early CT score change and functional outcome in a drip-and-ship stroke service

Location-specific ASPECTS does not improve Outcome Prediction in Large Vessel Occlusion compared to Cumulative ASPECTS

Simplified selection criteria for patients with longer or unknown time to treatment predict good outcome after mechanical thrombectomy

CT Reconstruction Levels Affect Automated and Reader-Based ASPECTS Ratings in Acute Ischemic Stroke

Clinical Utility of Electronic Alberta Stroke Program Early Computed Tomography Score Software in the ENCHANTED Trial Database

e-ASPECTS Correlates with and Is Predictive of Outcome after Mechanical Thrombectomy

Mobile stroke units for prehospital thrombolysis, triage, and beyond: benefits and challenges

First Automated Stroke Imaging Evaluation via Electronic Alberta Stroke Program Early CT Score in a Mobile Stroke Unit

Performance of e-ASPECTS software in comparison to that of stroke physicians on assessing CT scans of acute ischemic stroke patients