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AI that prioritizes critical care.

Computer vision that screens X-rays, MRIs, and CT scans in the background — flagging acute fractures, internal bleeding, and critical findings so emergency cases jump to the front of the queue.

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97%
Critical finding sensitivity
47s
Avg. AI analysis time
2.4M+
Scans processed
Review Queue Live
Intracranial Hemorrhage
Subdural, 3mm — CT Head
Critical
Acute Fracture
Left distal radius — X-Ray
Critical
Pulmonary Nodule
6mm, right upper lobe
Urgent
Routine Chest X-Ray
No acute findings
Routine
12 studies in queueAI updated 12s ago
IThe Challenge

Every second matters in critical care.

Radiologists face overwhelming backlogs. TriageMind puts life-threatening cases first.

The Challenge

Radiologists face overwhelming backlogs. Critical findings like acute fractures, intracranial hemorrhages, and pneumothoraces often wait hours behind routine studies — delaying life-saving treatment.

The TriageMind Solution

Our deep learning models analyze incoming X-rays, CTs, and MRIs in under 60 seconds — automatically flagging critical findings and reordering the review queue so emergency cases are read first.

Emergency Prioritization
47s Analysis
97% Sensitivity
📷 Scan Ingest
→
⚡ AI Analysis
→
🚨 Critical Flag
IIThe Diagnostic AI Stack

Four AI layers, one life-saving priority.

Transforming radiology workflow so what matters most is read first.

Multi-Modal Scan Analysis

Deep learning models trained on 2.4M+ annotated scans detect critical findings across X-ray, CT, and MRI — including fractures, hemorrhages, and pulmonary nodules.

CNN · Multi-Modal

Emergency Prioritization

AI assigns a criticality score to every incoming study — automatically reordering the PACS worklist so life-threatening cases are reviewed within minutes.

Prioritization Engine

Incidental Finding Detection

Beyond acute emergencies, AI flags incidental findings like lung nodules, aortic aneurysms, and early-stage cancers.

Incidental AI

Workflow & Analytics Dashboard

Real-time dashboard shows queue status, criticality distribution, and radiologist performance metrics.

Analytics
IIILive Review Queue

12 studies in queue, AI monitoring continuously.

LiveTriageMind Review Queue
Critical Urgent Routine
Queue Analytics
12
📊 Total Studies
3
🔴 Critical
4
🟡 Urgent
5
🟢 Routine
Top Findings
Acute Fracture
Left distal radius
Intracranial Hemorrhage
Subdural, 3mm
Lung Nodule
6mm, right upper lobe
IVThe Radiology Impact

Real outcomes from radiology departments.

97%

Critical finding sensitivity — reducing missed emergencies

74%

Faster read times for critical studies

47s

Average AI analysis time per study

2.4M+

Scans processed across global radiology networks

"Every minute saved in critical care diagnosis is a life that can be saved."

VWho We Serve

Built for radiology excellence.

TriageMind empowers every stakeholder in diagnostic imaging.

Radiologists

Focus on critical cases first. AI handles the triage so you can focus on diagnosis.

Hospitals & Health Systems

Reduce turnaround times, improve patient outcomes, and optimize radiology workflow.

Emergency Departments

Get critical results faster. TriageMind prioritizes ED imaging for life-saving decisions.

Imaging Centers

Differentiate your practice with AI-powered prioritization and quality assurance.

VIWhat Radiologists Say

Trusted by leading radiology departments.

★★★★★
"TriageMind flagged an acute subdural hemorrhage on a CT that was initially triaged as routine. The patient went to surgery within 45 minutes."
Dr. Micheal
Chief of Radiology, Mass General Brigham
★★★★★
"We've cut critical study turnaround times from 4+ hours to under 20 minutes. The AI's ability to detect subtle fractures is remarkable."
Dr. James
Director of Emergency Radiology, UCSF
★★★★★
"The incidental finding detection is a game-changer. We're catching early-stage cancers that would have been missed in the rush of the read."
Dr. Efrem
Chief of Breast Imaging, MD Anderson
VIIThe Diagnostic AI Team

Radiologists and researchers, united.

Radiologists, AI researchers, and data scientists united to save lives.

Dr. Anidi Samuel

Dr. Anidi Samuel

CEO & Co-Founder

Board-certified radiologist with 15+ years of clinical experience. Former faculty at Stanford.

Dr. M

Dr. Mary Mathew

CTO & Co-Founder

AI/ML Ph.D. specializing in medical imaging. Former lead at Google Health AI.

Dr. L

Dr. Linus Ochigbo

Head of Clinical Validation

Radiologist with expertise in AI model validation and FDA clearance processes.

D

Dorathy Ubafam

VP of Product

Product leader with deep experience in healthcare IT and PACS integration.

VIIIGet In Touch

Ready to prioritize critical care?

Tell us about your radiology practice, and we'll show you how TriageMind can help.

Email
info@triagemind.com
24/7 Support
+2349031581584
Address
Police Barracks, Saawuan Kpagh Street, Makurdi, Benue State
Urgent Clinical IntegrationFor rapid deployment in critical care settings, our implementation team is available for accelerated onboarding.+2349031581584
IXOnboarding Sequence

Start prioritizing critical care today.

Deploy TriageMind in your radiology practice in days. Start saving lives with AI-powered triage.

1

Connect

Integrate TriageMind with your existing PACS or imaging system in under 24 hours.

2

Analyze

Our AI automatically screens every incoming study — flagging critical findings in real-time.

3

Save

Critical cases jump to the front of the queue. Faster diagnosis, better outcomes.

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