Random Forests for multiclass classification: Random MultiNomial Logit
Expert Systems with Applications: An International Journal
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This paper presents a theoretical framework for the development of non-invasive methods for detection and discrimination between mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD). Growing use of IEDs and increased pace of multiple deployment cycles in current conflicts has lead to significant increases in exposure to risks for these conditions. Co-morbidity of these conditions is common, diagnostically challenging, and controversial. Development of easy to use, deployable diagnostic tools would allow for accurate early identification and intervention. Early intervention increases the potential for positive outcomes for both the individual and their families. In addition, the appropriately designed system could be used epidemiologically to screen returning soldiers for these conditions that may otherwise not be appropriately assessed until much later, if at all. The framework presented here proposes that a wireless, portable EEG/EKG based device may be an appropriate platform upon which to develop such an assessment tool.