Todd C. Campo

Date of Award


Document Type


Degree Name

Master of Science


Department of Operational Sciences

First Advisor

Daniel A. Pamplona, PhD


Military members in combat situations are at a high risk for experiencing a Traumatic Brain Injury (TBI), often leaving them with Post-Traumatic Headache (PTH). There is currently a poor understanding of what factors predict if a patient will endure acute (short-term) PTH or Persistent PTH (PPTH). The Concussion Assessment, Research, and Education (CARE) Consortium dataset contains a variety of pre-and-post-injury concussion assessments taken by NCAA athletes and service academy cadets between 2014 and 2018. Participants in this study (n = 1769) suffered a TBI. Using this longitudinal data, three models were constructed: an LSTM model using the raw assessment scores, a feed-forward Artificial Neural Network (ANN) model using extracted features, and an LSTM model using sequential extracted features. These models distinguished patients with PPTH from patients with acute PTH with Precision-Recall Area Under the Curve (PR-AUC) scores of 0.44, 0.47, and 0.46, respectively. This research has set the foundation for future studies of the CARE Consortium dataset or other TBI datasets to improve the prognosis of PPTH.

AFIT Designator



A 12-month embargo was observed.

Approved for public release. Case number on file.