Match tier
Listed
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-10-05
Biography and Research Information
OverviewAI-generated summary
Namarta Kapil's research focuses on understanding and improving diagnostic methods for developmental disorders, particularly cerebral palsy. She has investigated the predictive value of infant neurological examinations and the impact of training on inter-rater reliability for developmental assessments. Her work also explores the use of artificial intelligence in analyzing movement patterns for early detection of cerebral palsy in infants. Additionally, Kapil has contributed to research on drug delivery systems, specifically studying nanoliposomes for enhanced dermatokinetic attributes in preclinical models of rheumatoid arthritis. Her collaborations include work with Tara Johnson, Bittu Majmudar-Sheth, Alexa Celeste Escapita, and Bittu Majmudar at the University of Arkansas for Medical Sciences.
Metrics
- h-index: 3
- Publications: 8
- Citations: 69
Positions
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Postdoctoral Associate 2024–presentWashington University in St. Louis ORCID
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Postdoctoral Associate publications 2020–2025University of Arkansas for Medical Sciences ORCID
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PhD Candidate 2018–2023University of Arkansas for Medical Sciences Department of Neuroscience ORCID
Selected Publications
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Enhancing Detection of Cerebral Palsy: Multimodal Developmental Assessments in High-Risk Infants (2025)
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Unveiling the Immediate Impact of Prechtl’s General Movement Assessment Training on Inter-Rater Reliability and Cerebral Palsy Prediction (2024)
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Hammersmith Infant Neurological Examination Subscores Are Predictive of Cerebral Palsy (2023)
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Does Supine Lying Center of Pressure Movement Predict Normal Developmental Stages in Early Infancy? (2021)
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4107 Implementation and evaluation of a novel protocol that uses clinical biomarkers to promote early diagnosis and treatment of Neurodevelopmental Disabilities (2020)
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4108 Artificial Intelligence-Based Quantification of the General Movement Assessment Using Center of Pressure Patterns in Healthy Infants (2020)
Collaboration Network
Top Collaborators
Tara Johnson
University of Arkansas Medical Center
6 shared publications
In database
- Hammersmith Infant Neurological Examination Subscores Are Predictive of Cerebral Palsy
- Unveiling the Immediate Impact of Prechtl’s General Movement Assessment Training on Inter-Rater Reliability and Cerebral Palsy Prediction
- 4108 Artificial Intelligence-Based Quantification of the General Movement Assessment Using Center of Pressure Patterns in Healthy Infants
- Enhancing Detection of Cerebral Palsy: Multimodal Developmental Assessments in High-Risk Infants
- 4107 Implementation and evaluation of a novel protocol that uses clinical biomarkers to promote early diagnosis and treatment of Neurodevelopmental Disabilities
Showing 5 of 6 shared publications
Alexa Celeste Escapita
University of Arkansas for Medical Sciences
3 shared publications
In database
- Unveiling the Immediate Impact of Prechtl’s General Movement Assessment Training on Inter-Rater Reliability and Cerebral Palsy Prediction
- 4108 Artificial Intelligence-Based Quantification of the General Movement Assessment Using Center of Pressure Patterns in Healthy Infants
- Enhancing Detection of Cerebral Palsy: Multimodal Developmental Assessments in High-Risk Infants
Bittu Majmudar
Arkansas Children's Hospital
3 shared publications
In database
- 4108 Artificial Intelligence-Based Quantification of the General Movement Assessment Using Center of Pressure Patterns in Healthy Infants
- 4107 Implementation and evaluation of a novel protocol that uses clinical biomarkers to promote early diagnosis and treatment of Neurodevelopmental Disabilities
- Does Supine Lying Center of Pressure Movement Predict Normal Developmental Stages in Early Infancy?
Bittu Majmudar-Sheth
University of Arkansas Medical Center
3 shared publications
In database
- Hammersmith Infant Neurological Examination Subscores Are Predictive of Cerebral Palsy
- Unveiling the Immediate Impact of Prechtl’s General Movement Assessment Training on Inter-Rater Reliability and Cerebral Palsy Prediction
- Enhancing Detection of Cerebral Palsy: Multimodal Developmental Assessments in High-Risk Infants
Safeer F. Siddicky
Boise State University (US)
2 shared publications
- 4108 Artificial Intelligence-Based Quantification of the General Movement Assessment Using Center of Pressure Patterns in Healthy Infants
- Does Supine Lying Center of Pressure Movement Predict Normal Developmental Stages in Early Infancy?
Junsig Wang
University of Arkansas for Medical Sciences (US)
2 shared publications
- 4108 Artificial Intelligence-Based Quantification of the General Movement Assessment Using Center of Pressure Patterns in Healthy Infants
- Does Supine Lying Center of Pressure Movement Predict Normal Developmental Stages in Early Infancy?
Erin M. Mannen
Boise State University (US)
2 shared publications
- 4108 Artificial Intelligence-Based Quantification of the General Movement Assessment Using Center of Pressure Patterns in Healthy Infants
- Does Supine Lying Center of Pressure Movement Predict Normal Developmental Stages in Early Infancy?
Sowmya Sivakumar
University of Arkansas for Medical Sciences
2 shared publications
In database
- Enhancing Detection of Cerebral Palsy: Multimodal Developmental Assessments in High-Risk Infants
- 4107 Implementation and evaluation of a novel protocol that uses clinical biomarkers to promote early diagnosis and treatment of Neurodevelopmental Disabilities
Simon Chung
Arkansas Children's Hospital
1 shared publication
In database
- Enhancing Detection of Cerebral Palsy: Multimodal Developmental Assessments in High-Risk Infants
Andrew W. Brown
Arkansas Children's Hospital
1 shared publication
In database
- Enhancing Detection of Cerebral Palsy: Multimodal Developmental Assessments in High-Risk Infants
Similar Researchers
Based on overlapping research topics
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