scholarly journals Small Sample Deep Learning for Newborn Gestational Age Estimation

2017 ◽  
Author(s):  
Mercedes Torres Torres ◽  
Michel F. Valstar ◽  
Caroline Henry ◽  
Carole Ward ◽  
Don Sharkey
Keyword(s):  
Deep Learning ◽  
Gestational Age ◽  
Age Estimation ◽  
Small Sample ◽  
Gestational Age Estimation

scholarly journals Postnatal gestational age estimation of newborns using Small Sample Deep Learning

2019 ◽  
Vol 83-84 ◽  
pp. 87-99 ◽  
Author(s):  
Mercedes Torres Torres ◽  
Michel Valstar ◽  
Caroline Henry ◽  
Carole Ward ◽  
Don Sharkey
Keyword(s):  
Deep Learning ◽  
Gestational Age ◽  
Age Estimation ◽  
Small Sample ◽  
Gestational Age Estimation

scholarly journals Open-source, machine and deep learning-based automated algorithm for gestational age estimation through smartphone lens imaging

2018 ◽  
Vol 9 (12) ◽  
pp. 6038 ◽  
Author(s):  
Arjun D. Desai ◽  
Chunlei Peng ◽  
Leyuan Fang ◽  
Dibyendu Mukherjee ◽  
Andrew Yeung ◽  
...  
Keyword(s):  
Deep Learning ◽  
Open Source ◽  
Gestational Age ◽  
Age Estimation ◽  
Automated Algorithm ◽  
Gestational Age Estimation

scholarly journals Postnatal gestational age estimation using newborn screening blood spots: a proposed validation protocol

2017 ◽  
Vol 2 (2) ◽  
pp. e000365 ◽  
Author(s):  
Malia S Q Murphy ◽  
Steven Hawken ◽  
Katherine M Atkinson ◽  
Jennifer Milburn ◽  
Jesmin Pervin ◽  
...  
Keyword(s):  
Newborn Screening ◽  
Gestational Age ◽  
Age Estimation ◽  
Blood Spots ◽  
Gestational Age Estimation

scholarly journals External validation of postnatal gestational age estimation using newborn metabolic profiles in Matlab, Bangladesh

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Malia SQ Murphy ◽  
Steven Hawken ◽  
Wei Cheng ◽  
Lindsay A Wilson ◽  
Monica Lamoureux ◽  
...  
Keyword(s):  
Cord Blood ◽  
Gestational Age ◽  
Age Estimation ◽  
External Validation ◽  
Population Level ◽  
Average Deviation ◽  
Term Infants ◽  
Data Set ◽  
Heel Prick ◽  
Gestational Age Estimation

This study sought to evaluate the performance of metabolic gestational age estimation models developed in Ontario, Canada in infants born in Bangladesh. Cord and heel prick blood spots were collected in Bangladesh and analyzed at a newborn screening facility in Ottawa, Canada. Algorithm-derived estimates of gestational age and preterm birth were compared to ultrasound-validated estimates. 1036 cord blood and 487 heel prick samples were collected from 1069 unique newborns. The majority of samples (93.2% of heel prick and 89.9% of cord blood) were collected from term infants. When applied to heel prick data, algorithms correctly estimated gestational age to within an average deviation of 1 week overall (root mean square error = 1.07 weeks). Metabolic gestational age estimation provides accurate population-level estimates of gestational age in this data set. Models were effective on data obtained from both heel prick and cord blood, the latter being a more feasible option in low-resource settings.

scholarly journals Early termination of pregnancy: differences in gestational age estimation using last menstrual period and ultrasound in Mexico

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Biani Saavedra-Avendano ◽  
Raffaela Schiavon ◽  
Patricio Sanhueza ◽  
Ranulfo Rios-Polanco ◽  
Laura Garcia-Martinez ◽  
...  
Keyword(s):  
Gestational Age ◽  
Age Estimation ◽  
Termination Of Pregnancy ◽  
Early Termination ◽  
Menstrual Period ◽  
Last Menstrual Period ◽  
Gestational Age Estimation
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