Cargando…

Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study

BACKGROUND: Automated emotion classification could aid those who struggle to recognize emotions, including children with developmental behavioral conditions such as autism. However, most computer vision emotion recognition models are trained on adult emotion and therefore underperform when applied t...

Descripción completa

Detalles Bibliográficos
Autores principales:	Washington, Peter, Kalantarian, Haik, Kent, John, Husic, Arman, Kline, Aaron, Leblanc, Emilie, Hou, Cathy, Mutlu, Onur Cezmi, Dunlap, Kaitlyn, Penev, Yordan, Varma, Maya, Stockham, Nate Tyler, Chrisman, Brianna, Paskov, Kelley, Sun, Min Woo, Jung, Jae-Yoon, Voss, Catalin, Haber, Nick, Wall, Dennis Paul
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications 2022
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034430/ https://www.ncbi.nlm.nih.gov/pubmed/35394438 http://dx.doi.org/10.2196/26760

Ejemplares similares

Crowdsourced privacy-preserved feature tagging of short home videos for machine learning ASD detection
por: Washington, Peter, et al.
Publicado: (2021)

Crowd annotations can approximate clinical autism impressions from short home videos with privacy protections
por: Washington, Peter, et al.
Publicado: (2022)

Selection of trustworthy crowd workers for telemedical diagnosis of pediatric autism spectrum disorder
por: Washington, Peter, et al.
Publicado: (2021)

Precision Telemedicine through Crowdsourced Machine Learning: Testing Variability of Crowd Workers for Video-Based Autism Feature Recognition
por: Washington, Peter, et al.
Publicado: (2020)

Addendum to the Acknowledgements: Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks
por: Washington, Peter, et al.
Publicado: (2019)

Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks
por: Washington, Peter, et al.
Publicado: (2019)

Machine learning models using mobile game play accurately classify children with autism
por: Deveau, Nicholas, et al.
Publicado: (2022)

Feature Selection and Dimension Reduction of Social Autism Data
por: Washington, Peter, et al.
Publicado: (2020)

Identification of Social Engagement Indicators Associated With Autism Spectrum Disorder Using a Game-Based Mobile App: Comparative Study of Gaze Fixation and Visual Scanning Methods
por: Varma, Maya, et al.
Publicado: (2022)

The Performance of Emotion Classifiers for Children With Parent-Reported Autism: Quantitative Feasibility Study
por: Kalantarian, Haik, et al.
Publicado: (2020)

Feature replacement methods enable reliable home video analysis for machine learning detection of autism
por: Leblanc, Emilie, et al.
Publicado: (2020)

Estimating sequencing error rates using families
por: Paskov, Kelley, et al.
Publicado: (2021)

The human “contaminome”: bacterial, viral, and computational contamination in whole genome sequences from 1000 families
por: Chrisman, Brianna, et al.
Publicado: (2022)

Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder
por: Varma, Maya, et al.
Publicado: (2019)

A maximum flow-based network approach for identification of stable noncoding biomarkers associated with the multigenic neurological condition, autism
por: Varma, Maya, et al.
Publicado: (2021)

Localizing unmapped sequences with families to validate the Telomere-to-Telomere assembly and identify new hotspots for genetic diversity
por: Chrisman, Brianna, et al.
Publicado: (2023)

Transmission dynamics of human herpesvirus 6A, 6B and 7 from whole genome sequences of families
por: Chrisman, Brianna S., et al.
Publicado: (2022)

A Method for Localizing Non-Reference Sequences to the Human Genome
por: Chrisman, Brianna Sierra, et al.
Publicado: (2022)

Game theoretic centrality: a novel approach to prioritize disease candidate genes by combining biological networks with the Shapley value
por: Sun, Min Woo, et al.
Publicado: (2020)

Causal Modeling to Mitigate Selection Bias and Unmeasured Confounding in Internet-Based Epidemiology of COVID-19: Model Development and Validation
por: Stockham, Nathaniel, et al.
Publicado: (2022)

A Mobile Game Platform for Improving Social Communication in Children with Autism: A Feasibility Study
por: Penev, Yordan, et al.
Publicado: (2021)

Indels in SARS-CoV-2 occur at template-switching hotspots
por: Chrisman, Brianna Sierra, et al.
Publicado: (2021)

Improved detection of disease-associated gut microbes using 16S sequence-based biomarkers
por: Chrisman, Brianna S., et al.
Publicado: (2021)

Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study
por: Chi, Nathan A, et al.
Publicado: (2022)

Identification and Quantification of Gaps in Access to Autism Resources in the United States: An Infodemiological Study
por: Ning, Michael, et al.
Publicado: (2019)

Coalitional Game Theory Facilitates Identification of Non-Coding Variants Associated With Autism
por: Sun, Min Woo, et al.
Publicado: (2019)

Labeling images with facial emotion and the potential for pediatric healthcare
por: Kalantarian, Haik, et al.
Publicado: (2019)

Training and Profiling a Pediatric Facial Expression Classifier for Children on Mobile Devices: Machine Learning Study
por: Banerjee, Agnik, et al.
Publicado: (2023)

Coalitional game theory as a promising approach to identify candidate autism genes
por: Gupta, Anika, et al.
Publicado: (2018)

Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study
por: Tariq, Qandeel, et al.
Publicado: (2019)

Mobile detection of autism through machine learning on home video: A development and prospective validation study
por: Tariq, Qandeel, et al.
Publicado: (2018)

Racial and Ethnic Disparities in Geographic Access to Autism Resources Across the US
por: Liu, Bennett M., et al.
Publicado: (2023)

A Low Rank Model for Phenotype Imputation in Autism Spectrum Disorder
por: Paskov, Kelley M., et al.
Publicado: (2018)

Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism
por: Daniels, Jena, et al.
Publicado: (2018)

Comparing Computed Tomography–Derived Augmented Reality Holograms to a Standard Picture Archiving and Communication Systems Viewer for Presurgical Planning: Feasibility Study
por: Dallas-Orr, David, et al.
Publicado: (2020)

Topic modeling for multi-omic integration in the human gut microbiome and implications for Autism
por: Tataru, Christine, et al.
Publicado: (2023)

Neurostimulation for Traumatic Brain Injury: Emerging Innovation
por: Diaz, Michael Joseph, et al.
Publicado: (2023)

Feasibility of a Secure Wireless Sensing Smartwatch Application for the Self-Management of Pediatric Asthma
por: Hosseini, Anahita, et al.
Publicado: (2017)

Longitudinal study of stool-associated microbial taxa in sibling pairs with and without autism spectrum disorder
por: Tataru, Christine, et al.
Publicado: (2021)

Multitask learning improves prediction of cancer drug sensitivity
por: Yuan, Han, et al.
Publicado: (2016)

Cannot write session to /tmp/vufind_sessions/sess_5o4hnsr1csk3fk9tp3ftuigqnj