title: Multimodal predictor of neurodevelopmental outcome in newborns with hypoxic-ischaemic encephalopathy.
abstract: Automated multimodal prediction of outcome in newborns with hypoxic-ischaemic encephalopathy is investigated in this work. Routine clinical measures and 1h EEG and ECG recordings 24h after birth were obtained from 38 newborns with different grades of HIE. Each newborn was reassessed at 24 months to establish their neurodevelopmental outcome. A set of multimodal features is extracted from the clinical, heart rate and EEG measures and is fed into a support vector machine classifier. The performance is reported with the statistically most unbiased leave-one-patient-out performance assessment routine. A subset of informative features, whose rankings are consistent across all patients, is identified. The best performance is obtained using a subset of 9 EEG, 2h and 1 clinical feature, leading to an area under the ROC curve of 87% and accuracy of 84% which compares favourably to the EEG-based clinical outcome prediction, previously reported on the same data. The work presents a promising step towards the use of multimodal data in building an objective decision support tool for clinical prediction of neurodevelopmental outcome in newborns with hypoxic-ischaemic encephalopathy.
authors.affiliation: Department of Electrical and Electronic Engineering, University College Cork, Ireland; Neonatal Brain Research Group, INFANT Research Centre, University College Cork, Ireland. Electronic address: atemko@ucc.ie.
authors.forename: Andriy
authors.initials: A
authors.lastname: Temko
authors.affiliation: Department of Neuroimaging, Institute of Psychiatry, King׳s College London, London, UK. Electronic address: orla.doyle@kcl.ac.uk.
authors.forename: Orla
authors.initials: O
authors.lastname: Doyle
authors.affiliation: Department of Pediatrics and Child Health, University College Cork, Ireland; Neonatal Brain Research Group, INFANT Research Centre, University College Cork, Ireland. Electronic address: d.murray@ucc.ie.
authors.forename: Deirdre
authors.initials: D
authors.lastname: Murray
authors.affiliation: Department of Electrical and Electronic Engineering, University College Cork, Ireland; Neonatal Brain Research Group, INFANT Research Centre, University College Cork, Ireland. Electronic address: g.lightbody@ucc.ie.
authors.forename: Gordon
authors.initials: G
authors.lastname: Lightbody
authors.affiliation: Department of Pediatrics and Child Health, University College Cork, Ireland; Neonatal Brain Research Group, INFANT Research Centre, University College Cork, Ireland. Electronic address: g.boylan@ucc.ie.
authors.forename: Geraldine
authors.initials: G
authors.lastname: Boylan
authors.affiliation: Department of Electrical and Electronic Engineering, University College Cork, Ireland; Neonatal Brain Research Group, INFANT Research Centre, University College Cork, Ireland. Electronic address: l.marnane@ucc.ie.
authors.forename: William
authors.initials: W
authors.lastname: Marnane
mesh_terms: D016208:Databases, Factual; D004562:Electrocardiography; D004569:Electroencephalography; D005260:Female; D006801:Humans; D020925:Hypoxia-Ischemia, Brain / Q000503:physiopathology*; D007231:Infant, Newborn; D007232:Infant, Newborn, Diseases / Q000503:physiopathology*; D008297:Male; D011237:Predictive Value of Tests; D060388:Support Vector Machine
keywords: Decision support system; ECG; EEG; Multimodal; Neonatal; Neurodevelopmental; Outcome