Credentials: Ph.D. Student, Psychology
Research Interests: Machine Learning & Precision Medicine
Addiction Research Center: arc.psych.wisc.edu
Research Advisor: Dr. John Curtin
Personal Website: Gaylen Fronk
Follow me on ResearchGate
Broadly, my research focuses on applying contemporary machine learning approaches to advance precision medicine in the use of pharmacological treatments for substance use disorders. Precision medicine offers an approach whereby treatments are designed and selected to optimize their therapeutic benefit for particular subgroups of patients based on unique individual differences. Machine learning approaches are well-suited to accommodate high-dimensional arrays of predictors to extract reliable prediction signals that generalize robustly to new samples of patients. Ultimately, I hope to develop prospective treatment-matching models that will allow for immediate implementation in clinical practice with immediate benefits to patients to minimize the gap between clinical science and real-world treatment.
Machine learning algorithms for precision medicine in smoking cessation
Bradford DE, Fronk GE, Sant’Ana SJ, Magruder KP, Kaye JT & Curtin JJ (2018). The need for precise answers for the goals of precision medicine in alcohol dependence to succeed. Neuropsychopharmacology, 43(9): 1799-1800. DOI: 10.1038/s41386-018-0112-y
Smith MA, Fronk GE, Abel JM, Lacy RT, Bills SE & Lynch WJ (2018). Resistance exercise decreases heroin self-administration and alters gene expression in the nucleus accumbens of heroin-exposed rats. Psychopharmacology, 235(4): 1245-1255. DOI: 10.1007/s00213-018-4840-9.
Robinson AM, Fronk GE, Zhang H, Tonidandel S & Smith MA (2017). The effects of social contact on cocaine intake in female rats. Drug and Alcohol Dependence, 177: 48-53. DOI: 10.1016/j.drugalcdep.2017.03.027.
Smith MA, Fronk GE, Zhang H, Magee CP & Robinson AM (2016). Acute bouts of wheel running decrease cocaine self-administration: Influence of exercise output. Pharmacology, Biochemistry & Behavior, 150-151: 94-99. DOI: 10.1016/j.pbb.2016.10.001.