Federico A. Galatolo

ORCID: 0000-0001-7193-3754 · 2 papers in corpus

article 2023

Application of Deep Learning Model in the Sonographic Diagnosis of Uterine Adenomyosis

International journal of environmental research and public health ·doi:10.3390/ijerph20031724

BACKGROUND: This study aims to evaluate the diagnostic performance of Deep Learning (DL) machine for the detection of adenomyosis on uterine ultrasonographic images and compare it to intermediate ultrasound skilled trainees. METHODS: Prosp…

preprint 2022

Application of deep learning model in the sonographic diagnosis of uterine adenomyosis

·doi:10.21203/rs.3.rs-2176240/v1

Abstract Purpose: To evaluate the diagnostic performance of Deep Learning (DL) machine for the detection of adenomyosis on uterine ultrasonographic images and compare it to intermediate ultrasound skilled trainees. Methods: Prospective obse…