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Classical And Neural Network Machine Learning To Determine The Risk Of Marijuana Use, Laura Zoboroski [*], Torrey J. Wagner, Brent T. Langhals
Classical And Neural Network Machine Learning To Determine The Risk Of Marijuana Use, Laura Zoboroski [*], Torrey J. Wagner, Brent T. Langhals
Faculty Publications
Marijuana is the most commonly abused drug for military personnel tested at the Air Force Drug Testing Laboratory. A publicly available dataset of drug use, personality trait scores and demographic data was modeled with logistic regression, decision tree and neural network models to determine the extent to which marijuana use can be predicted using personality traits. While the logistic regression model had lower performance than the neural network model, it matched the sensitivity of prior work (0.80), achieved a high level of significance (p < 0.05) and yielded valuable inferences. It implied that younger, less educated individuals who exhibit sensation-seeking behavior and are open to experience tend to be at higher risk for THC use. A method for performing an iterative multidimensional neural network hyperparameter search is presented, and two iterations of a 6-dimensional search were performed. Metrics were used to select a family of 8 promising models from a cohort of 4600 models, and the best NN model’s 0.87 sensitivity improved upon the literature. The model met an f1 overfitting threshold on the test and holdout datasets, and an accuracy sensitivity analysis on a holdout-equivalent dataset yielded a 95% CI of 0.86 ± 0.04. These results have the potential to increase the efficacy of drug prevention and intervention programs.
Role Of The Endocannabinoid System And Medical Cannabis, Sabrina Jarvis, Sean Rassmussen, Blaine A. Winters
Role Of The Endocannabinoid System And Medical Cannabis, Sabrina Jarvis, Sean Rassmussen, Blaine A. Winters
Faculty Publications
Our bodies produce complex substrates called endocannabinoids, which attach to the endocannabinoid system (ECS) receptors and impact many physiologic processes. Current research on the ECS and cannabis-based medications is accelerating in the presence of continued conflict between federal and state laws. In this article we present a summary of the latest information on the ECS, its receptors, and current research on the cannabis-based medicines and their potential to treat various disease pathologies and medical conditions. Our study includes the latest information on the continued legal ramifications nurse practitioners face in treating patients with these medications.