Catching what radiology reports can't afford to miss
Azra AI automatically surfaces high-risk oncologic incidental findings from radiology reports, prioritizing patients, eliminating manual review, and routing them to the right care pathway before time runs out.
The Problem
Millions of incidental findings. Most go untracked.
Radiologists flag unexpected findings every day: pulmonary nodules, adrenal masses, hepatic lesions. But without a system to track, prioritize, and route these findings, patients fall through the cracks. The result is delayed diagnoses, avoidable late-stage cancer, and preventable deaths.
Up to 40% of incidental findings never receive follow-up care
Lost in report queues, missed by overwhelmed care teams, and disconnected from downstream workflows.
Delayed follow-up is the #1 malpractice driver in radiology
Manual processes simply cannot scale to the volume of cross-sectional imaging performed today.
of lung cancer patients are diagnosed at Stage III or IV, when survival rates drop below 20%. Earlier detection changes everything.
The average lag between an incidental pulmonary nodule finding and a definitive cancer diagnosis in unmanaged health systems.
5-year survival rate for lung cancer detected at Stage I. Azra AI finds them early.
Automated Workflow
From report to care, automatically
Azra AI ingests HL7/FHIR messages directly from your EHR, processes them in real time, and routes patients into the right care pathway, all without manual intervention.
Report Ingestion
Radiology reports stream in via HL7/FHIR from Cerner, Epic, or any source system. No manual uploads, no delays.
Real-TimeAI Extraction & Classification
Advanced NLP identifies incidental findings, including location, size, density, margins, and nodule count, with clinical precision.
<2% False PositivesRisk Stratification
Each finding is scored using evidence-based risk calculators and predictive AI models. High-risk patients surface immediately.
Evidence-BasedCare Coordination
Patients are automatically enrolled in the right surveillance or treatment pathway. Human-in-the-loop review keeps clinicians in control.
AutomatedDisease Programs
One platform. Every cancer type.
Azra AI's incidental finding programs span the full oncology landscape, each built on disease-specific AI models, evidence-based risk calculators, and guideline-aligned care pathways. Not just lung.
Lung
Pulmonary nodules & incidental findings
Automated Lung-RADS scoring and Fleischner Society adherence. Longitudinal nodule tracking across studies. Risk stratification with <2% false positives. The flagship program, proven at scale.
Breast
Incidental findings
Surfaces incidental breast findings buried in chest and abdominal imaging. Incidental Detection.
Pancreas
Cysts, masses & ductal dilation
Pancreatic incidentalomas are among the most under-followed findings in radiology. Azra AI catches cysts, masses, and main duct dilation, applying ACG and AGA guidelines to stratify surgical urgency.
Liver
Hepatic lesions & HCC surveillance
LI-RADS classification applied automatically to incidental hepatic lesions. Flags indeterminate lesions needing follow-up.
Renal
Renal masses & cystic lesions
Bosniak classification automated for incidental renal cysts and masses.
GYN
Ovarian & uterine incidental findings
Ovarian and adnexal lesions found incidentally on abdominal and pelvic imaging.
Neuro
Cancerous and Benign lesions
Identifies incidental intracranial masses and spine findings on head and neck imaging.
Custom Models
Built to your specifications
Have a disease area or clinical workflow that doesn't fit a standard template? Azra AI builds custom AI models and care pathways tailored to your institution, from adrenal incidentalomas to thyroid nodules and beyond.
EHR Integration
Zero double documentation. Every action written back.
Clinicians shouldn't have to document in Azra AI and then re-enter the same data into Epic or Cerner. They don't. Azra AI seamlessly populates discrete EHR fields and sends every navigation activity back into the patient's chart automatically.
- Discrete field population Risk scores, finding classifications, and stage data written directly into structured EHR fields, not free text.
- Navigation activities sent back To Epic, Cerner, or any HL7/FHIR-compatible system in real time.
- Bi-directional sync Chart updates in the EHR surface back into Azra AI, keeping both systems in agreement.
- Full audit trail in both systems Every AI recommendation and clinician decision is timestamped and stored.
Paired with Azra AI Pathology Models
From suspicion to survivorship, in a single platform
When radiology flags an incidental finding, that's the beginning of a patient's journey, not the end. Paired with Azra AI's pathology models, you can follow every patient from that first suspicious nodule all the way through diagnosis, treatment, and long-term survivorship. One platform. No handoffs lost.
Incidental Finding
AI surfaces a suspicious nodule from a routine CT. Risk score generated instantly. Patient flagged for follow-up.
Risk Stratification
Lung-RADS, radiomics, and clinical AI converge. High-risk patients surface to the top, with <2% false positives.
Biopsy & Pathology
Azra AI's pathology models process tissue specimens, extracting diagnosis, grade, margin status, and biomarker eligibility.
Diagnosis & Staging
Malignancy confirmed. Stage assigned. Genomic test eligibility flagged. MDM case review automatically triggered.
Treatment Routing
Patient transitioned to oncology or surgery, with full clinical record, imaging history, and pathology in one place.
Survivorship Program
Post-treatment surveillance, recurrence monitoring, and outcomes tracking, in the same platform that found them on day one.
No other platform follows a patient from suspicion to survivorship.
Most oncology AI tools solve one problem. Azra AI connects the entire patient journey. When the radiology model finds a nodule and the pathology model confirms a malignancy, the same platform that flagged the finding enrolls the patient in survivorship. No care gaps. No dropped handoffs. No lost patients.
Measured Impact
Lives saved. Measured in data.
Every metric below represents a patient who was found earlier, treated sooner, and given a better chance at survival.
Stage I Survival Rate
When lung cancer is caught before it spreads.
Faster to Treatment
Vs. standard unmanaged follow-up.
Fewer Lost to Follow-Up
Patients who would otherwise fall through the cracks.
“The incidental finding that gets lost in a report queue is the cancer that kills someone five years later. Azra AI closes that gap, systematically, at scale, across every report.”EVP Care Management, NCI Designated Cancer Center
Ready to follow every patient from suspicion to survivorship?
See how Azra AI's radiology and pathology models work together in a single platform, from the first incidental finding to long-term survivorship care.