OC10.11: The data science of obstetric ultrasound: automatic analysis of full‐length anomaly scans using machine learning algorithms

Fri, 16 Oct 2020 00:00:00 +0000

BibTex

@article{doi:10.1002/uog.22275,
author = {Drukker, L. and Sharma, H. and Droste, R. and Noble, J.A. and Papageorghiou, A.T.},
title = {OC10.11: The data science of obstetric ultrasound: automatic analysis of full-length anomaly scans using machine learning algorithms},
journal = {Ultrasound in Obstetrics \& Gynecology},
volume = {56},
number = {S1},
pages = {31-31},
doi = {10.1002/uog.22275},
url = {https://obgyn.onlinelibrary.wiley.com/doi/abs/10.1002/uog.22275},
eprint = {https://obgyn.onlinelibrary.wiley.com/doi/pdf/10.1002/uog.22275},
year = {2020}
}

Monitoring Sonographer Performance: The Perception Ultrasound by Learning Sonographer Experience (PULSE) study

Mon, 01 Apr 2019 00:00:00 +0000

Data science | Harshita Sharma

OC10.11: The data science of obstetric ultrasound: automatic analysis of full‐length anomaly scans using machine learning algorithms

BibTex

Monitoring Sonographer Performance: The Perception Ultrasound by Learning Sonographer Experience (PULSE) study