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AI-Powered Radiology

AI-assisted radiology, Built for Independent Imaging

Urgent American Radiology Services helps independent imaging centers and underserved communities adopt radiologist-overseen AI workflows for screening mammography, chest X-ray triage, and reporting automation.
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AI-assisted workflows
PACS / RIS integration
Radiologist-overseen
Built for independent imaging centers
HIPAA-aligned
Underserved-access focus
Platform

AI-assisted radiology workflows in a single operational layer.

No slow scrolling demo, no hidden cards. The core product surfaces are visible at a glance, with radiologist oversight, worklist control, reporting automation, and QA feedback loops presented clearly for buyers.

01
Mammography AI workflow

Screening mammography support with worklist prioritization, suspicious-finding flagging, and structured handoff to radiologist review.

  • Suspicious-finding overlays with radiologist confirmation.
  • Density-aware worklist routing.
02
Chest X-ray triage

AI-assisted CXR triage that prioritizes potentially urgent studies and routes them through radiologist confirmation.

  • Critical-finding alerts with SLA timers.
  • Configurable rules per modality and shift.
03
NLP & reporting automation

Structured report drafting, key-image selection, and macro-aware language that radiologists review, edit, and finalize.

  • Macro-aware draft reports.
  • Key-image selection candidates.
04
Worklist prioritization

Risk-stratified worklist with configurable rules, SLA tracking, and integration into existing reading queues.

  • Drop-in compatibility with existing queues.
  • Subspecialty and shift-aware ordering.
05
Quality analytics

Override rates, recall metrics, turnaround time, and peer-review analytics — all visible to your QA leads.

  • Turnaround, override, and recall dashboards.
  • Per-radiologist and per-modality cuts.
06
Patient & referrer follow-up

Integrate with patient communication and referrer-notification systems for closed-loop follow-up on actionable findings.

  • Closed-loop recall on actionable findings.
  • Referrer-notification handoffs.
By the numbers

Outcomes modeled on industry benchmarks

0+

Imaging sites served (target deployment)

0%*

Increase in detection rate (industry benchmark)

0M+

Studies orchestrated per year (target volume)

<0 h

Interpretation SLA target

*Reference values modeled on industry benchmarks; not a guarantee of clinical performance.
Implementation priorities

What matters before an AI workflow goes live.

01
Radiologist control

AI assists with triage, prioritization, and drafting. Final interpretation stays with the radiologist.

02
Workflow-first integration

Built to fit around existing PACS, RIS, reporting, and communication systems instead of replacing them.

03
Measurable operations

Turnaround, overrides, recall workflows, and QA signals are captured so leadership can see what changed.

Evidence preview

Selected publications on AI in radiology and mammography

Mammography
2023
Landmark
Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study
Lång K, Josefsson V, Larsson A-M, et al. · The Lancet Oncology

Randomised, controlled trial in Swedish population screening showing AI-supported single reading was non-inferior to standard double reading for cancer detection while reducing radiologist screen-reading workload by ~44%.

View on publisher →
Mammography
2020
Landmark
International evaluation of an AI system for breast cancer screening
McKinney SM, Sieniek M, Godbole V, et al. · Nature

Google Health / DeepMind model evaluated on UK and US screening datasets reduced false positives and false negatives versus radiologists, and generalised across populations.

View on publisher →
Mammography
2019
Landmark
Stand-alone artificial intelligence for breast cancer detection in mammography: comparison with 101 radiologists
Rodriguez-Ruiz A, Lång K, Gubern-Merida A, et al. · Journal of the National Cancer Institute

Stand-alone AI achieved cancer detection performance comparable to the average of 101 radiologists across nine reader studies.

View on publisher →
Trusted by independent imaging centers

Partner imaging centers and radiology groups across the U.S.

Bayside Imaging
Coastal Radiology Group
Heartland Diagnostics
Pacific Breast Center
Summit Imaging
Atlas Radiology
Northstar MRI
Pinecrest Imaging
Bayside Imaging
Coastal Radiology Group
Heartland Diagnostics
Pacific Breast Center
Summit Imaging
Atlas Radiology
Northstar MRI
Pinecrest Imaging
Insights

Field notes on AI-assisted radiology

Perspective pieces from the team, plus operator playbooks for independent imaging centers.

All insights →
Field guide
7 min read

What independent imaging centers actually need from AI in 2026

A field guide to the AI workflow patterns that move the needle on turnaround time, recall management, and read-cost economics — and the ones that don't.

Bring AI-assisted radiology to your center

Talk to Urgent American Radiology Services about a workflow assessment for your imaging center, radiology group, or community-health partnership.

Request a Workflow Assessment
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AI-assisted, radiologist-overseen workflows — built for independent imaging centers, radiology groups, and the communities they serve.

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