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MIDI (MR Imaging Abnormality Deep Learning Identification)

NCT04368481 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 30000

Last updated 2024-04-10

No results posted yet for this study

Summary

The study involves the development and testing of an artificial intelligence (AI) tool that can identify abnormalities using patient head scans conducted for routine clinical care and research volunteer scans. A deep learning algorithm will be developed using a dataset of retrospective and prospective MRI head scans to train, validate, and test convolutional networks using software developed at the Department of Biomedical Engineering, King's College London. The reference standard will be consultant radiologist reports of the MRI head scans.

Conditions

  • Neurological Disorder

Sponsors & Collaborators

Principal Investigators

  • Thomas Booth · King's College Hospital NHS Trust

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-04-01
Primary Completion
2024-08-31
Completion
2025-03-31

Countries

  • United Kingdom

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04368481 on ClinicalTrials.gov