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Providing data so computer systems can help with the early identification of lung diseases, leading to more rapid treatment and better survival rates

The integration and analysis of Data using Artificial intelligence to impRove patient outcomes with Thoracic diseases

Status
Recruiting
Phases
Unknown
Study type
Unknown
Source
ISRCTN
Registry ID
ISRCTN13720905
Enrollment
300000
Registered
2022-04-07
Start date
2020-10-01
Completion date
Unknown
Last updated
2022-05-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Early diagnosis of lung cancer Cancer

Interventions

Data will be collected retrospectively from Lung Health Check centres, with patient consent. There will be no impact on patient care.

Sponsors

Research Governance, Ethics & Assurance Team (RGEA), University of Oxford
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Participants attending NHSE targeted lung health checks

Exclusion criteria

Exclusion criteria: Patients who request to not be included in any studies as part of the NHS opt out.

Design outcomes

Primary

MeasureTime frame
1. Diagnosis of cancer measured by expert opinion using Targeted Lung Health Check spreadsheets and CT scans, collected from patients attending lung health checks first visit. 2. Diagnosis of cancer measured by AI model using Digital images collected from the CT scan.—

Secondary

MeasureTime frame
1. Diagnosis of cancer determined by expert histology opinion from resection and biopsy specimens 2. Diagnosis of cancer determined by the AI model from the digitised resection and biopsy specimens—

Countries

England, United Kingdom

Outcome results

None listed

Source: ISRCTN (via WHO ICTRP) · Data processed: Feb 4, 2026