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1.
Predicting low cognitive ability at age 5 years using perinatal data and machine learning.
Pediatr Res
; 95(6): 1634-1643, 2024 May.
Article
in English
| MEDLINE | ID: mdl-38177251
2.
Big data, machine learning, and population health: predicting cognitive outcomes in childhood.
Pediatr Res
; 93(2): 300-307, 2023 01.
Article
in English
| MEDLINE | ID: mdl-35681091
3.
Clinical implementation of a neonatal seizure detection algorithm.
Decis Support Syst
; 70: 86-96, 2015 Feb.
Article
in English
| MEDLINE | ID: mdl-25892834
4.
Prediction of 2-Year Cognitive Outcomes in Very Preterm Infants Using Machine Learning Methods.
JAMA Netw Open
; 6(12): e2349111, 2023 Dec 01.
Article
in English
| MEDLINE | ID: mdl-38147334
5.
Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy.
Sci Data
; 10(1): 129, 2023 03 10.
Article
in English
| MEDLINE | ID: mdl-36899033
6.
Predicting Low Cognitive Ability at Age 5-Feature Selection Using Machine Learning Methods and Birth Cohort Data.
Int J Public Health
; 67: 1605047, 2022.
Article
in English
| MEDLINE | ID: mdl-36439276
7.
Towards Deeper Neural Networks for Neonatal Seizure Detection.
Annu Int Conf IEEE Eng Med Biol Soc
; 2021: 920-923, 2021 11.
Article
in English
| MEDLINE | ID: mdl-34891440
8.
Grading hypoxic-ischemic encephalopathy in neonatal EEG with convolutional neural networks and quadratic time-frequency distributions.
J Neural Eng
; 18(4)2021 03 19.
Article
in English
| MEDLINE | ID: mdl-33618337
9.
Deep Learning for EEG Seizure Detection in Preterm Infants.
Int J Neural Syst
; 31(8): 2150008, 2021 Aug.
Article
in English
| MEDLINE | ID: mdl-33522460
10.
In vitro evaluation of delays in the adjustment of the fraction of inspired oxygen during CPAP: effect of flow and volume.
Arch Dis Child Fetal Neonatal Ed
; 106(2): 205-207, 2021 Mar.
Article
in English
| MEDLINE | ID: mdl-32796056
11.
Neonatal seizure detection from raw multi-channel EEG using a fully convolutional architecture.
Neural Netw
; 123: 12-25, 2020 Mar.
Article
in English
| MEDLINE | ID: mdl-31821947
12.
Identifying tracé alternant activity in neonatal EEG using an inter-burst detection approach.
Annu Int Conf IEEE Eng Med Biol Soc
; 2020: 5984-5987, 2020 07.
Article
in English
| MEDLINE | ID: mdl-33019335
13.
Grading the severity of hypoxic-ischemic encephalopathy in newborn EEG using a convolutional neural network.
Annu Int Conf IEEE Eng Med Biol Soc
; 2020: 6103-6106, 2020 07.
Article
in English
| MEDLINE | ID: mdl-33019363
14.
Suitability of an inter-burst detection method for grading hypoxic-ischemic encephalopathy in newborn EEG.
Annu Int Conf IEEE Eng Med Biol Soc
; 2019: 4125-4128, 2019 Jul.
Article
in English
| MEDLINE | ID: mdl-31946778
15.
Prediction of short-term health outcomes in preterm neonates from heart-rate variability and blood pressure using boosted decision trees.
Comput Methods Programs Biomed
; 180: 104996, 2019 Oct.
Article
in English
| MEDLINE | ID: mdl-31421605
16.
Investigating the Impact of CNN Depth on Neonatal Seizure Detection Performance.
Annu Int Conf IEEE Eng Med Biol Soc
; 2018: 5862-5865, 2018 Jul.
Article
in English
| MEDLINE | ID: mdl-30441669
17.
Heart Rate Variability during Periods of Low Blood Pressure as a Predictor of Short-Term Outcome in Preterms.
Annu Int Conf IEEE Eng Med Biol Soc
; 2018: 5614-5517, 2018 Jul.
Article
in English
| MEDLINE | ID: mdl-30441609
18.
Coupling between mean blood pressure and EEG in preterm neonates is associated with reduced illness severity scores.
PLoS One
; 13(6): e0199587, 2018.
Article
in English
| MEDLINE | ID: mdl-29933403
19.
Gaussian process modeling of EEG for the detection of neonatal seizures.
IEEE Trans Biomed Eng
; 54(12): 2151-62, 2007 Dec.
Article
in English
| MEDLINE | ID: mdl-18075031
20.
Local model network identification with Gaussian processes.
IEEE Trans Neural Netw
; 18(5): 1404-23, 2007 Sep.
Article
in English
| MEDLINE | ID: mdl-18220189