AIMC Topic: Developmental Disabilities
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Automated extraction of functional biomarkers of verbal and ambulatory ability from multi-institutional clinical notes using large language models.
Journal of neurodevelopmental disorders
Apr 30, 2025
BACKGROUND: Functional biomarkers in neurodevelopmental disorders, such as verbal and ambulatory abilities, are essential for clinical care and research activities. Treatment planning, intervention monitoring, and identifying comorbid conditions in i...
CNVDeep: deep association of copy number variants with neurocognitive disorders.
BMC bioinformatics
Aug 29, 2024
BACKGROUND: Copy number variants (CNVs) have become increasingly instrumental in understanding the etiology of all diseases and phenotypes, including Neurocognitive Disorders (NDs). Among the well-established regions associated with ND are small part...
Understanding COVID-19 infection among people with intellectual and developmental disabilities using machine learning.
Disability and health journal
Mar 15, 2024
BACKGROUND: People with intellectual and developmental disabilities (IDD) were disproportionately affected by the COVID-19 pandemic. Predicting COVID-19 infection has been difficult.
Socially assistive robotics and older family caregivers of young adults with Intellectual and Developmental Disabilities (IDD): A pilot study exploring respite, acceptance, and usefulness.
PloS one
Sep 12, 2022
INTRODUCTION: The need for caregiver respite is well-documented for the care of persons with IDD. Social Assistive Robotics (SAR) offer promise in addressing the need for caregiver respite through 'complementary caregiving' activities that promote en...
Understanding Emotions in Children with Developmental Disabilities during Robot Therapy Using EDA.
Sensors (Basel, Switzerland)
Jul 7, 2022
Recent technological advancements have led to the emergence of supportive robotics to help children with developmental disabilities become independent. In conventional research, in robot therapy, experiments are often conducted by operating the robot...
A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants.
Scientific reports
Sep 15, 2020
Survivors following very premature birth (i.e., ≤ 32 weeks gestational age) remain at high risk for neurodevelopmental impairments. Recent advances in deep learning techniques have made it possible to aid the early diagnosis and prognosis of neurodev...
Feed-forward neural networks using cerebral MR spectroscopy and DTI might predict neurodevelopmental outcome in preterm neonates.
European radiology
Jul 18, 2020
OBJECTIVES: We aimed to evaluate the ability of feed-forward neural networks (fNNs) to predict the neurodevelopmental outcome (NDO) of very preterm neonates (VPIs) at 12 months corrected age by using biomarkers of cerebral MR proton spectroscopy (H-M...
Diffusion Tensor Imaging
Infant, Premature, Diseases
Sensitivity and Specificity
Male
Infant
Predictive Value of Tests
Image Interpretation, Computer-Assisted
Brain
Infant, Premature
Prognosis
Developmental Disabilities
Humans
Female
Magnetic Resonance Spectroscopy
Neural Networks, Computer
Infant, Newborn
Prospective Studies
A preliminary evaluation of still face images by deep learning: A potential screening test for childhood developmental disabilities.
Medical hypotheses
Jun 7, 2020
Most developmental disorders are defined by their clinical symptoms and many disorders share common features. The main objective of this research is to evaluate still facial images as a potential screening test for childhood developmental disabilitie...
GEARing smart environments for pediatric motor rehabilitation.
Journal of neuroengineering and rehabilitation
Feb 10, 2020
BACKGROUND: There is a lack of early (infant) mobility rehabilitation approaches that incorporate natural and complex environments and have the potential to concurrently advance motor, cognitive, and social development. The Grounded Early Adaptive Re...
Computational modeling of interventions for developmental disorders.
Psychological review
Jun 6, 2019
We evaluate the potential of connectionist models of developmental disorders to offer insights into the efficacy of interventions. Based on a range of computational simulation results, we assess factors that influence the effectiveness of interventio...
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