Evaluation of artificial intelligence algorithms for detecting various pathologies across multiple diagnostic modalities including medical imaging (X-ray, CT, MRI, ultrasound) and other diagnostic tools (e.g., electrocardiograms). Specific conditions will be defined at the sub-study level. Other
Conditions
Interventions
Data Collection: Anonymised medical diagnostic test datasets (imaging and other diagnostic investigations) collected from routine clinical care via Electronic Patient Records (EPR) and clinical IT sys
Sponsors
Oxford University Hospitals NHS Trust
Eligibility
Sex/Gender
All
Age
2 Years to 120 Years
Inclusion criteria
Inclusion criteria: Since this is a data-only retrospective study, there are no direct participant inclusion criteria. Rather, the inclusion criteria apply to the imaging/diagnostic data:? 1. Anonymised medical diagnostic investigations (imaging or diagnostic tests) obtained as part of routine clinical care 2. Diagnostic data that can be anonymised without compromising data integrity 3. Images/tests meeting quality standards for AI algorithm analysis
Exclusion criteria
Exclusion criteria: 1. Imaging or diagnostic investigations where data cannot be anonymised or where anonymisation compromises data integrity 2. National Data Opt-Out: Data from patients listed in the National Data Opt-Out database who have formally opted out of having their data shared for research purposes 3. Substudy-specific exclusions: Additional exclusion criteria (e.g., age restrictions, specific imaging modality requirements, or pathology-specific criteria) that are dependent on individual substudies
Countries
England, United Kingdom
Contacts
Public ContactAbdala T Espinosa Morgado
Outcome results
None listed