TY - JOUR
T1 - General movement assessment by machine learning
T2 - why is it so difficult?
AU - Schmidt, William Thomas
AU - Regan, Matthew
AU - Fahey, Michael C
AU - Paplinski, Andrew
N1 - Publisher Copyright:
© Journal of Medical Artificial Intelligence. All rights reserved.
PY - 2019/7
Y1 - 2019/7
N2 - The current rate of cerebral palsy (CP) per live births in Australia is between 0.14% and 0.2%, worldwide the rate has been static for 60 years at 0.2%. Typically a CP diagnosis is delayed until around age 2 years; this delay decreases the likelihood of a long-term positive patient outcome. Current early detection is by visual examination of newborns 10 to 20 weeks post gestation. A screening program based on filming babies and processing the video via artificial intelligence (AI) will allow increased early detection and intervention. This paper outlines the practical development, and initial results from, a recurrent deep neural net solution for the classification of newborn videos, specifically targeting CP, using the largest fidgety movements dataset in Australia.
AB - The current rate of cerebral palsy (CP) per live births in Australia is between 0.14% and 0.2%, worldwide the rate has been static for 60 years at 0.2%. Typically a CP diagnosis is delayed until around age 2 years; this delay decreases the likelihood of a long-term positive patient outcome. Current early detection is by visual examination of newborns 10 to 20 weeks post gestation. A screening program based on filming babies and processing the video via artificial intelligence (AI) will allow increased early detection and intervention. This paper outlines the practical development, and initial results from, a recurrent deep neural net solution for the classification of newborn videos, specifically targeting CP, using the largest fidgety movements dataset in Australia.
KW - Cerebral palsy (CP)
KW - Convolution neural networks
KW - Deep neural networks
KW - Early intervention
KW - Fidgety movements
KW - Long short-term networks
UR - http://www.scopus.com/inward/record.url?scp=85091045582&partnerID=8YFLogxK
U2 - 10.21037/jmai.2019.06.02
DO - 10.21037/jmai.2019.06.02
M3 - Review Article
AN - SCOPUS:85091045582
VL - 2
JO - Journal of Medical Artificial Intelligence
JF - Journal of Medical Artificial Intelligence
SN - 2617-2496
IS - July
M1 - 15
ER -