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Pulmonology Workspace

AI-assisted chest X-ray analysis for pulmonary care teams.

Trained on large-scale chest imaging datasets, the NorthNeuron Pulmonology workspace helps radiologists and pulmonologists identify clinically significant findings faster with confidence scores, visual heatmaps, and fully traceable results.

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Chest Imaging AI

Conditions Supported

Six clinically significant findings. One chest X-ray workflow.

Infectious Disease

Tuberculosis (TB) Screening

AI-assisted TB pattern detection for high-volume screening programs.

Supports TB screening initiatives with AI analysis trained on diverse international chest X-ray datasets including frontal and lateral views. Designed to help radiologists prioritise high-probability cases in resource-constrained settings.

Pulmonary

Pneumonia & Airspace Opacity

Detection of airspace consolidation and opacity patterns.

Identifies airspace consolidation, ground-glass opacity, and infiltrates consistent with pneumonia or infectious processes helping triage teams flag cases that warrant immediate clinical review.

Pleural

Pleural Effusion

Identification of pleural fluid accumulation across imaging views.

Detects unilateral and bilateral pleural effusions across frontal chest projections, supporting early identification of fluid build-up in patients with cardiac, renal, or oncological conditions.

Urgent

Pneumothorax

Pneumothorax detection with confidence scoring for urgent triage.

AI-assisted detection of air in the pleural space supporting rapid triage prioritisation for a time-critical emergency. Confidence-scored outputs highlight cases that demand immediate clinical attention.

Cardiac & Pulmonary

Pulmonary Edema & Congestion

Analysis of patterns consistent with fluid overload and congestion.

Identifies radiographic features of pulmonary edema including vascular redistribution, Kerley lines, and interstitial changes supporting earlier recognition in cardiac and renal patient populations.

Pulmonary

Atelectasis

Recognition of lobar and segmental atelectasis patterns.

Detects volume loss and collapse patterns across lobar and segmental regions supporting post-operative monitoring, airway obstruction evaluation, and general chest imaging review workflows.

For Radiologists & Pulmonologists

AI that works the way your review workflow does.

  • Pre-read AI support reduces time-to-finding for high-volume chest imaging programs.
  • Confidence-scored outputs highlight cases that warrant closer clinical attention so the urgent cases surface first.
  • Visual heatmaps show which regions of the image drove each AI finding.
  • Structured finding summaries are reviewable, auditable, and ready to inform the clinical record.
  • Multi-finding analysis in a single review six conditions assessed from one uploaded chest X-ray.

Built for Scale

From single clinics to national screening programs.

  • Handles high-volume imaging queues without compromising per-case analysis quality.
  • Designed for de-identified workflows no patient identifiers required.
  • Enterprise-grade access controls and full audit logging for institutional compliance.
  • Supports multi-site deployment across hospital networks and radiology groups.

Ready to Elevate Your Chest Imaging Workflow?

Bring AI-assisted pulmonary analysis to your radiology team.

Start with a pilot evaluation across your real imaging cases. We'll work with your clinical team to define success criteria and demonstrate measurable value.

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