Artificial intelligence is no longer a future concept in respiratory and sleep medicine. It is already embedded in the daily workflows of clinical physiology labs, quietly improving how scientists collect data, how doctors write reports, and how patients receive care. In labs using Rezibase, AI-assisted reporting is not a pilot programme or a roadmap item. It is a working feature reshaping how respiratory and sleep data is reviewed, interpreted, and communicated today.

TL;DR

• AI is actively being used in respiratory and sleep labs for staging, scoring, and report writing right now, not just in research settings.

• Rezibase integrates AI-powered report writing and structural algorithms directly into its pulmonary function test software.

• New research shows AI can predict over 100 health conditions from sleep data alone, signalling how central sleep lab management software will become to preventive care.

• For labs, the practical benefits are fewer errors, faster turnaround, and reduced clinical risk.

• The AI features in Rezibase are built around real clinical workflows, not retrofitted from generic tools.

About the Author: This article was written by the Rezibase team, respiratory and sleep reporting specialists with over 37 years of combined experience in clinical physiology. Rezibase is purpose-built by respiratory scientists and is trusted by over 35 sites across Australia and the United Kingdom, including NHS and NSW Health facilities.

What Is AI Actually Doing in Respiratory and Sleep Labs Right Now?

AI in clinical physiology has moved well past the research phase. According to a 2026 scoping review published in npj Primary Care Respiratory Medicine, AI is rapidly advancing respiratory disease management across the full care pathway, from diagnosis through to population lung health [The rise of artificial intelligence in respiratory primary care and pulmonology: a scoping review | npj Primary Care Respiratory Medicine]. Similarly, published research in sleep medicine confirms AI is currently being applied to sleep staging, respiratory event scoring, insomnia characterisation, and circadian rhythm prediction [Artificial intelligence in sleep medicine: Present and future - PMC].

In practical terms, this means:

• Automated sleep staging that reduces manual scoring time for scientists

• Respiratory event detection applied to overnight studies

• Report structuring algorithms that guide doctors toward guideline-compliant language

• AI-assisted dictation and writing tools that convert clinical observations into structured reports

These are not experimental features. They are happening in labs today.

How Does Rezibase Use AI in Its Reporting Workflow?

Rezibase integrates AI directly into the reporting process through two key mechanisms: AI-powered report writing and algorithm-driven report structuring based on ATS (American Thoracic Society) guidelines.

Rather than leaving doctors to write reports from scratch, the platform provides:

• A structured list of reports queued for each doctor to review

• Medical dictation support built into the workflow

• AI-assisted writing that converts clinical data into coherent, formatted report language

• Algorithmic checks that align report outputs with ATS standards

This matters because the quality of a respiratory report depends not just on the data but on how clearly and consistently it is communicated. AI in this context is not replacing clinical judgement. It is reducing the cognitive load on clinicians and eliminating structural inconsistencies that can create clinical risk.

Why Does AI Matter More in Sleep Medicine Right Now?

Sleep data has become unexpectedly valuable beyond its original diagnostic purpose. In January 2026, Stanford Medicine researchers published findings on an AI model capable of predicting more than 100 health conditions using data collected during sleep studies [New AI model predicts disease risk while you sleep]. That is a significant finding, and it points toward a future where sleep lab management software is not just an administrative tool but a front line of preventive medicine.

For labs managing overnight studies, this raises a practical question: is your current system capable of capturing, storing, and integrating the kind of granular sleep data that emerging AI models will need to function?

Rezibase is cloud-based and vendor-neutral, meaning it can receive data from any device manufacturer. That architecture positions labs to participate in data-rich workflows without being locked into a single equipment ecosystem.

What Makes AI-Assisted Reporting Different from Just Better Software?

This is a fair question. Not all automation is AI, and the distinction matters.

AI-assisted reporting learns from patterns in clinical language and data. It does not simply fill in a form. This is why platforms like Rezibase, which embed these tools into the actual reporting workflow rather than bolting them on as a separate module, produce a more seamless experience for scientists and doctors.

How Does Rezibase Handle Data Import for AI-Assisted Workflows?

A consistent challenge in clinical physiology is getting data from devices into reporting systems without transcription errors. Rezibase addresses this through its Magic Import feature, which pulls device reports directly into the platform and automatically extracts discrete data points, including flow-volume loops.

This matters for AI workflows because:

• Clean, structured data is a prerequisite for accurate AI analysis

• Manual data entry introduces errors that corrupt downstream reporting

• Vendor-neutral import means labs are not forced to change equipment to use the platform

For labs considering how to prepare for expanded AI use, data quality and data accessibility are the starting points. Rezibase is designed around both.

Frequently Asked Questions

Is AI in respiratory reporting accurate enough to use in real clinical settings?
Yes, and it is already being used. Research published in 2026 confirms AI is advancing rapidly in respiratory disease management across diagnosis and population health applications [The rise of artificial intelligence in respiratory primary care and pulmonology: a scoping review | npj Primary Care Respiratory Medicine]. The key is that AI tools in platforms like Rezibase assist clinicians rather than replace their judgement.

Does Rezibase replace respiratory scientists with AI?
No. Rezibase is built by respiratory scientists specifically to support the work of respiratory scientists. AI features reduce repetitive tasks and structural errors, freeing scientists to focus on clinical analysis.

Can Rezibase integrate with our existing hospital systems?
Yes. Rezibase integrates with Patient Administration Systems, Electronic Medical Records, DICOM Modality Worklists, Hospital Finance Systems, and Electronic Orders Systems.

What if we switch to Rezibase from another platform like Respiro?
Moving to Rezibase is designed to be straightforward. The team supports data migration with a clear process, and because the platform is cloud-based, there is no complex local infrastructure to rebuild. Most labs find the transition simpler than expected.

Is Rezibase only for respiratory, or does it cover sleep as well?
Both. Rezibase covers respiratory and sleep under one platform, which is relatively uncommon in this space. This makes it a comprehensive solution for labs running both service types.

How does Rezibase handle ATS guideline compliance in reporting?
ATS-aligned algorithms are built into the reporting workflow. Reports are structured and checked against guideline standards automatically, reducing the risk of non-compliant outputs.

Is there a trial available before committing?
Yes. Rezibase offers a 30-day free trial with no lock-in contracts and transparent all-inclusive monthly pricing.

About Rezibase

Rezibase is Australia's most advanced cloud-based respiratory and sleep reporting solution, built by respiratory scientists Peter Rochford and the late Jeff Pretto, and now backed by healthcare technology company Cardiobase. Trusted by over 35 sites including NHS and NSW Health facilities, Rezibase delivers a vendor-neutral, enterprise-grade platform covering the full patient lifecycle from referral through to accreditation. With over 37 years of experience behind the platform and a mission to improve patient care through technology, Rezibase is purpose-built for the real-world needs of clinical physiology labs across Australia, New Zealand, the United Kingdom, and Ireland.

Ready to see AI-assisted reporting in action in your lab? Visit rezibase.com to start your free 30-day trial or speak with the team about what Rezibase can do for your respiratory and sleep service.