Pre-Specialist X-ray Triage
A clinical decision support tool for primary care and urgent care clinics that runs a chest X-ray through a local model and flags 'needs urgent specialist review' for possible TB, pneumonia, or mass — helping clinicians without on-site radiology decide who to refer.
Primary care physicians and nurse practitioners in clinics without on-site radiology
- Local inference returns probability of pneumonia, TB, mass, or normal with confidence
- Triage recommendation: 'refer urgently' vs. 'routinely manage' with the evidence highlighted
- Side-by-side comparison if a prior X-ray is uploaded, flagging interval change
- Date-stamped prediction log for the clinical record and downstream audit
Global radiologist shortage plus rising respiratory disease burden means primary care clinics read more imaging than they can confidently handle.
Radiologist shortage and imaging backlogs are well-documented globally (e.g., Canadian MRT vacancy spikes in 2025, global radiology reporting backlogs), confirming primary care clinics carry more imaging interpretation than they can confidently handle.Health Workforce Crisis Report - Canadian Association of Medical Radiation Technologists ↗Backlogs in formal interpretation of radiology examinations: a pilot study ↗
Chest X-ray AI triage is a crowded FDA-cleared category (Aidoc, Lunit, Annalise, Viz.ai; >1,100 AI-enabled radiology devices cleared as of early 2026), but almost all target radiologist worklists rather than primary-care clinicians without on-site radiology — a meaningful but narrow niche.FDA-Cleared AI Diagnostic Tools: What's Working in Radiology ↗List of FDA-Cleared AI Radiology Triage Software Vendors ↗Comprehensive Chest X-ray AI Detection Software | Lunit ↗
Healthcare SaaS CDSS benchmarks run $200–$800/provider/month, but most PCPs and rural/urgent-care clinics operate on thin margins and radiology AI vendors historically sell into hospital budgets, not individual clinics — willingness-to-pay for a triage flag (not a diagnosis) is meaningfully lower than the starting score assumes.Healthcare SaaS Solutions 2026 | Complete Guide for Practice Leaders ↗Healthcare SaaS Pricing: HIPAA-Compliant Tiers & Benchmarks ↗
Structural radiologist shortage, rising global TB and pneumonia burden, and a mature FDA clearance pathway for radiology AI support a multi-decade market — longevity is strong, though capped slightly because the value prop is triage/referral rather than diagnosis replacement.Artificial Intelligence for Tuberculosis Screening and Detection - MDPI ↗Artificial Intelligence-Enabled Medical Devices | FDA ↗
Building a local on-prem chest X-ray triage model is technically straightforward with open models, but competing with FDA-cleared incumbents (Aidoc, Lunit) requires millions in clinical validation and regulatory spend that an indie team is unlikely to clear; 'local model' deployment adds further ops complexity versus cloud incumbents.Aidoc Receives FDA Breakthrough Device Designation for AI That Drafts Radiology Reports ↗FDA-Cleared AI Diagnostic Tools: What's Working in Radiology ↗