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Validation of a Mobile App for Remote Autism Screening in Toddlers.

Publication ,  Journal Article
Krishnappa Babu, PR; Di Martino, JM; Aiello, R; Eichner, B; Espinosa, S; Green, J; Howard, J; Perochon, S; Spanos, M; Vermeer, S; Dawson, G; Sapiro, G
Published in: NEJM AI
October 2024

Early detection of autism is important for timely access to diagnostic evaluation and early intervention services, which improve children's outcomes. Despite the ability of clinicians to reliably diagnose autism in toddlers, diagnosis is often delayed. SenseToKnow is a mobile autism screening application (app) delivered on a smartphone or tablet that provides an objective and quantitative assessment of early behavioral signs of autism based on computer vision (CV) and machine learning (ML). This study examined the accuracy of SenseToKnow for autism detection when the app was downloaded and administered remotely at home by caregivers using their own devices. The SenseToKnow app was administered by caregivers of 620 toddlers between 16 and 40 months of age, 188 of whom were subsequently diagnosed with autism by expert clinicians. The app displayed strategically designed movies and a bubble-popping game on an iPhone or iPad while recording the child's behavioral responses through the device's front-facing camera and touch/inertial sensors. Recordings of the child's behavior were then automatically analyzed using CV. Multiple behavioral phenotypes were quantified and combined using ML in an algorithm for autism prediction. SenseToKnow demonstrated a high level of diagnostic accuracy with area under the receiver operating characteristic curve of 0.92, sensitivity of 83.0%, specificity of 93.3%, positive predictive value of 84.3%, and negative predictive value of 92.6%. Accuracy of the app for detecting autism was similar when administered on either a caregiver's iPhone or iPad. These results demonstrate that a mobile autism screening app based on CV can be delivered remotely by caregivers at home on their own devices and can provide a high level of accuracy for autism detection. Remote screening for autism potentially lowers barriers to autism screening, which could reduce disparities in early access to services and support and improve children's outcomes.

Duke Scholars

Published In

NEJM AI

DOI

EISSN

2836-9386

Publication Date

October 2024

Volume

1

Issue

10

Location

United States
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Krishnappa Babu, P. R., Di Martino, J. M., Aiello, R., Eichner, B., Espinosa, S., Green, J., … Sapiro, G. (2024). Validation of a Mobile App for Remote Autism Screening in Toddlers. NEJM AI, 1(10). https://doi.org/10.1056/AIcs2400510
Krishnappa Babu, Pradeep Raj, J Matias Di Martino, Rachel Aiello, Brian Eichner, Steven Espinosa, Jennifer Green, Jill Howard, et al. “Validation of a Mobile App for Remote Autism Screening in Toddlers.NEJM AI 1, no. 10 (October 2024). https://doi.org/10.1056/AIcs2400510.
Krishnappa Babu PR, Di Martino JM, Aiello R, Eichner B, Espinosa S, Green J, et al. Validation of a Mobile App for Remote Autism Screening in Toddlers. NEJM AI. 2024 Oct;1(10).
Krishnappa Babu, Pradeep Raj, et al. “Validation of a Mobile App for Remote Autism Screening in Toddlers.NEJM AI, vol. 1, no. 10, Oct. 2024. Pubmed, doi:10.1056/AIcs2400510.
Krishnappa Babu PR, Di Martino JM, Aiello R, Eichner B, Espinosa S, Green J, Howard J, Perochon S, Spanos M, Vermeer S, Dawson G, Sapiro G. Validation of a Mobile App for Remote Autism Screening in Toddlers. NEJM AI. 2024 Oct;1(10).

Published In

NEJM AI

DOI

EISSN

2836-9386

Publication Date

October 2024

Volume

1

Issue

10

Location

United States