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Artificial Intelligence-Based Machine Learning to Diagnose and Classify Adenomyosis from Ultrasound Scans: a Multicentre Model Development Study
Sponsor: CARE Fertility UK
Summary
The aim of this study is to use the vast dataset of annotated ultrasound images of normal uterus and of adenomyosis of varying severity to train a neural network using deep learning framework (Pytorch) and automated machine learning tool (Vertex AI). The main question it aims to answer are: 1. Diagnostic performance of automated (Google Vertex AI (Artificial intelligence) vision) and deep learning (Pytorch) machine learning model 2. Time saved in assessment of adenomyosis per healthcare professional
Official title: Artificial Intelligence-Based Machine Learning to Classify Adenomyosis from Ultrasound Scans: a Multicentre Model Development Study
Key Details
Gender
FEMALE
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
10000
Start Date
2024-06-04
Completion Date
2026-02-06
Last Updated
2025-01-09
Healthy Volunteers
No
Conditions
Interventions
use of deep learning and automated machine learning to diagnose and classify adenomyosis
Vertex AI Vision V1 software will be used as an automated machine learning tool and Pytorch 2.5 as deep learning framework. The complete set of reviewed, formatted and labelled images will be uploaded and split manually into two different datasets in 9:1 ratio; 90% of the selected images will be used as training dataset (training + validation) and 10% as test dataset.
Locations (1)
CARE Fertility
Birmingham, England, United Kingdom