Last reviewed · How we verify

NCT04897178: MARS

Machine Learning-based Anomaly Recognition System

Status unknown Last updated 25 May 2021
What this trial tests

trial testing Ultrasound in Fetal Anomaly in 1,000 participants. Status unknown.

Timeline
1 June 2021
Primary endpoint
1 May 2022
1 December 2023

Quick facts

Lead sponsorAssiut University
StatusStatus unknown
Study typeOBSERVATIONAL
Enrollment1,000
Start date1 June 2021
Primary completion1 May 2022
Estimated completion1 December 2023
Sites2 locations across Egypt

Drugs / interventions tested

Conditions studied

Sponsor

Assiut University

Who can join

Adults 18 to 45, female only, with Fetal Anomaly. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

MARS is an artificial intelligence-powered system that aims at detecting common fetal anomalies during real-time obstetrics ultrasound. The current study comprises 2 stages: (1) The stage of model creation which will include retrospective collection of images from fetal anatomy scans with known diagnoses to train these model and test their diagnostic accuracy. (2) The stage of model validation through prospective application of this model to collected videos with known normal and abnormal diagnoses

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

Verify or expand the search:

Other trials of Ultrasound

Trials testing the same drug.

Other recruiting trials for Fetal Anomaly

Currently open trials in the same condition.

Other Assiut University trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT04897178.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing