Deep-learning-based markerless tracking of distal anatomical landmarks in clinically recorded videos for assessing infant movement patterns associated with neurodevelopmental status

Deep learning-based quantitative analyses of spontaneous movements and their association with early neurological development in preterm infants

(2022) Hyun Iee Shin et al.   Scientific Reports

Development and Validation of a Deep Learning Method to Predict Cerebral Palsy From Spontaneous Movements in Infants at High Risk

(2022) Daniel Groos et al.   JAMA Network Open

Automated Movement Analysis to Predict Cerebral Palsy in Very Preterm Infants: An Ambispective Cohort Study

(2022) Kamini Raghuram et al.   Children-Basel

MacaquePose: A Novel “In the Wild” Macaque Monkey Pose Dataset for Markerless Motion Capture

(2021) Rollyn Labuguen et al.   Frontiers in Behavioral Neuroscience

OptiFlex: Multi-Frame Animal Pose Estimation Combining Deep Learning With Optical Flow

(2021) XiaoLe Liu et al.   Frontiers in Cellular Neuroscience

Towards human-level performance on automatic pose estimation of infant spontaneous movements

(2021) Daniel Groos et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms

(2021) Roxana Daneshjou et al.   JAMA Dermatology

Early Motor Development Predicts Clinical Outcomes of Siblings at High-Risk for Autism: Insight from an Innovative Motion-Tracking Technology

(2020) Angela Caruso et al.   Brain Sciences

Using DeepLabCut for 3D markerless pose estimation across species and behaviors

(2019) Tanmay Nath et al.   Nature Protocols

Fully automated image-based estimation of postural point-features in children with cerebral palsy using deep learning

(2019) Ryan Cunningham et al.   Royal Society Open Science

The Pooled Diagnostic Accuracy of Neuroimaging, General Movements, and Neurological Examination for Diagnosing Cerebral Palsy Early in High-Risk Infants: A Case Control Study

(2019) Catherine Morgan et al.   Journal of Clinical Medicine

A new deep learning-based method for the detection of gait events in children with gait disorders: Proof-of-concept and concurrent validity

(2019) Mathieu Lempereur et al.   JOURNAL OF BIOMECHANICS

Behavioral tracking gets real

(2018) Kunlin Wei et al.   NATURE NEUROSCIENCE

DeepLabCut: markerless pose estimation of user-defined body parts with deep learning

(2018) Alexander Mathis et al.   NATURE NEUROSCIENCE

Animal studies of neonatal hypothermic neuroprotection have translated well in to practice

(2015) Alistair J. Gunn et al.   RESUSCITATION

Early Diagnosis and Early Intervention in Cerebral Palsy

(2014) Mijna Hadders-Algra   Frontiers in Neurology

A systematic review of tests to predict cerebral palsy in young children

(2013) Margot Bosanquet et al.   DEVELOPMENTAL MEDICINE AND CHILD NEUROLOGY

Cerebral palsy: the whys and hows

(2012) Charlie Fairhurst   Archives of Disease in Childhood-Education and Practice Edition

Predictive validity of Prechtl’s Method on the Qualitative Assessment of General Movements: a systematic review of the evidence

(2011) VASILIKI DARSAKLIS et al.   DEVELOPMENTAL MEDICINE AND CHILD NEUROLOGY

Predicting Motor Development in Very Preterm Infants at 12 Months' Corrected Age: The Role of Qualitative Magnetic Resonance Imaging and General Movements Assessments

(2009) A. J. Spittle et al.   PEDIATRICS