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Assessment of the Clinical and Workflow Benefits of an Artificial Intelligence Based System for the Semi-Automated Caliper Placement and Measurements of Fetal Neurosonogram
Pilots
Feasibility and Validation of an Artificial Intelligence Based Software to Mimic a Clinically Relevant Approach for Anatomical Assessment of 2D Fetal Neurosonogram Video Loops
Pilots
The role of artificial intelligence in screening and democratizing quality prenatal care: A retrospective validation on sonograms of fetal brain
Clinical Validation
Leveraging clinically relevant biometric constraints to supervise a deep learning model for the accurate caliper placement to obtain sonographic measurements of the fetal brain
Clinical Validation
A deep learning system for the automated quantification and screening of suspected ventriculomegaly from 2D ultrasound images of the fetal brain
Clinical Validation
Development and validation of an artificial intelligence based system for the automated detection of choroid plexus cyst from fetal cranial sonograms
Clinical Validation
Towards a device-independent deep learning approach for the automated segmentation of sonographic fetal brain structures
Clinical Validation
A Clinically-Interpretable Artificial Intelligence Based System to Automatically Detect “Lemon Sign” on Fetal Cranial Sonograms
Clinical Validation
A Deep Learning System for the Automated Calliper Placement to Measure Multiple Fetal Brain Structures from Two-Dimensional Ultrasound Images
Clinical Validation
A Multicentre, Multi-Device Validation of a Deep Learning System for the Automated Segmentation of Fetal Brain Structures
Clinical Validation
Artificial Intelligence System (AIS) to Automatically Obtain Multiple Key Sonographic Measurements of the Fetal Brain in the Axial Views
Clinical Validation
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