Predicting Traumatic Brain Injury Through Behavioral Pattern Analysis in Youth with Autism

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Madhuhasa Battula Practicum Poster.pdf (604.62 KB)
Date
2023-08
Authors
Battula, Madhuhasa
Neal, Tiffany
Deodhar, Aditi
Swiezy, Naomi
Language
American English
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Abstract

This practicum, conducted at HANDS in Autism® in collaboration with the Indiana NeuroDiagnostic Institute (NDI), explored the relationship between patient behavioral profiles and the presence of Traumatic Brain Injury (TBI) in individuals with Autism Spectrum Disorder (ASD). Using a combination of pre-admission data from Cerner and post-discharge data from REDCap, a comprehensive dataset of 58 patients was coded and analyzed to identify behavioral patterns. Prediction models, including Logistic Regression and Random Forest, were developed in Python to assess the likelihood of TBI based on specific behavior indicators. Results revealed statistically significant correlations between certain behavioral patterns and the presence of TBI. This work supports the potential for predictive modeling to improve early identification and intervention strategies for patients with ASD and co-occurring neurological conditions.

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Keywords
Autism, Autism Spectrum Disorder (ASD), Individuals with ASD, Inpatient Psychiatry, Traumatic Brain Injury (TBI), Behavioral Health Analytics, Evidence-Based Practices (EBP), Neurodevelopmental Disorders, Behavioral Pattern Recognition, Predictive Modeling
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Cite As
Battula, M., Neal, T., Deodhar, A., & Swiezy, N. (2023). Predicting Traumatic Brain Injury Through Behavioral Pattern Analysis in Youth with Autism. Presented at the Summer 2023 Poster Session, Luddy School of Informatics, Computing, and Engineering, Department of Biomedical Engineering and Informatics, Indiana University Indianapolis. †
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https://hdl.handle.net/1805/47726
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