User profiles for "author:Elizabeth Palmer"

Elizabeth Emma Palmer

- Verified email at health.nsw.gov.au - Cited by 2504

Elizabeth Palmer Kelly

- Verified email at osumc.edu - Cited by 884

Elizabeth M. Palmer

- Verified email at usc.edu - Cited by 339

Automated detection of ADHD: Current trends and future perspective

HW Loh, CP Ooi, PD Barua, EE Palmer… - Computers in Biology …, 2022 - Elsevier
Attention deficit hyperactivity disorder (ADHD) is a heterogenous disorder that has a
detrimental impact on the neurodevelopment of the brain. ADHD patients exhibit …

[HTML][HTML] Artificial intelligence enabled personalised assistive tools to enhance education of children with neurodevelopmental disorders—a review

PD Barua, J Vicnesh, R Gururajan, SL Oh… - International Journal of …, 2022 - mdpi.com
Mental disorders (MDs) with onset in childhood or adolescence include
neurodevelopmental disorders (NDDs)(intellectual disability and specific learning …

[HTML][HTML] Application of deep learning models for automated identification of Parkinson's disease: A review (2011–2021)

HW Loh, W Hong, CP Ooi, S Chakraborty, PD Barua… - Sensors, 2021 - mdpi.com
Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting
over 6 million people globally. Although there are symptomatic treatments that can increase …

PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework

AJM Dingemans, M Hinne, KMG Truijen, L Goltstein… - Nature Genetics, 2023 - nature.com
Several molecular and phenotypic algorithms exist that establish genotype–phenotype
correlations, including facial recognition tools. However, no unified framework that …

[HTML][HTML] Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders

T Wang, K Hoekzema, D Vecchio, H Wu… - Nature …, 2020 - nature.com
Most genes associated with neurodevelopmental disorders (NDDs) were identified with an
excess of de novo mutations (DNMs) but the significance in case–control mutation burden …

Automated ASD detection using hybrid deep lightweight features extracted from EEG signals

M Baygin, S Dogan, T Tuncer, PD Barua… - Computers in Biology …, 2021 - Elsevier
Background Autism spectrum disorder is a common group of conditions affecting about one
in 54 children. Electroencephalogram (EEG) signals from children with autism have a …

Epilepsy detection in 121 patient populations using hypercube pattern from EEG signals

I Tasci, B Tasci, PD Barua, S Dogan, T Tuncer… - Information …, 2023 - Elsevier
Background Epilepsy is one of the most commonly seen neurologic disorders worldwide
and has generally caused seizures. Electroencephalography (EEG) is widely used in …

Association of shared decision-making on patient-reported health outcomes and healthcare utilization

TM Hughes, K Merath, Q Chen, S Sun, E Palmer… - The American Journal of …, 2018 - Elsevier
Background Shared decision-making (SDM) is a process that respects the rights of patients
to be fully involved in decisions about their care. By evaluating all available healthcare …

Delivery of dark material to Vesta via carbonaceous chondritic impacts

V Reddy, L Le Corre, DP O'Brien, A Nathues… - Icarus, 2012 - Elsevier
NASA's Dawn spacecraft observations of Asteroid (4) Vesta reveal a surface with the highest
albedo and color variation of any asteroid we have observed so far. Terrains rich in low …

Automated accurate detection of depression using twin Pascal's triangles lattice pattern with EEG Signals

G Tasci, HW Loh, PD Barua, M Baygin, B Tasci… - Knowledge-Based …, 2023 - Elsevier
Electroencephalogram (EEG)-based major depressive disorder (MDD) machine learning
detection models can objectively differentiate MDD from healthy controls but are limited by …