An AI-enabled NHS lung cancer pathway can reduce patient CT wait times from weeks to minutes, free up valuable radiological resources, and save outsourcing costs by up to 70%.

Watch Simon Rasalingham, CEO of Behold.ai, describe the red dot ® Lung Cancer Detection Platform to Matt Whitty, CEO of Accelerated Access Collaborative.

Our red dot® platform can seamlessly integrate into the NHS lung cancer pathway

Speed up lung cancer diagnosis

CXRs identified as SLC are prioritised for hot-reporting and patient is fast-tracked for a same-day or next day CT Chest examination.

Increase radiology capacity

CXRs identified as HCN (normal with a very high degree of confidence) are autonomously reported, reducing radiology workload and reliance on outsourcing.

How does our red dot® Chest X-Ray solution perform?

15%

saving in radiologist workload

15% of CXRs auto-reported as normal, instantly removing them from the reporting workload

70%

reduction in outsourcing costs

Our AI rule-out normal algorithm can reduce outsourcing costs by up to 70%

0.33%

Error rate reporting CXRs as Normal

compared to 13.5% for consultant radiologists

60%

reduction in missed lung cancer cases

when implementing red dot® triage alongside consultant radiologists

Our evidence

“Diagnosis of normal chest X-rays using an autonomous deep learning algorithm” published in Clinical Radiology: We demonstrated that red dot® was capable of auto-reporting 15% of all CXRs as normal with an error rate of just 0.33%. This is compared to an average error rate of 13.5% for consultant radiologists.

“Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance” published in Clinical Radiology: We demonstrated that in a tumour-enriched dataset implementing red dot® triage alongside consultant radiologists resulted in an overall reduction of missed lung cancer by 60%.

Read our case studies

The clinical need for red dot® is clear...

Leading cause of death worldwide

2m
fatalities every year – lung cancer is the leading cause of cancer-related deaths worldwide

Biggest in the UK

#1
cause of cancer-related deaths in the UK but second most common malignancy

Long waiting list

274,000
patients estimated in the UK waiting 11 days or more for a report on imaging studies

An AI enabled pathway not only significantly reduces time to treatment but also reduces costs and increases radiological resources

£6.8m

saved per year

on outsourcing costs

39,000+

hours

of reporting time put back into the NHS through the delivery of HCN flags – the equivalent of 19 consultant radiologists

+60%

CTH scans identified as normal

Patients who have no acute clinical abnormality, with an NPV of 93%, and remove >60.65% of all CTH scans from the reporting workload.

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