Senior undergraduate student, Adeola Obembe, and Dr. Emily Hendryx have teamed up with cardiologist Dr. Stavros Stavrakis at OUHSC to conduct research at the interface of mathematics/statistics and medicine. The goal of their work is to develop models predictive of patient response to a non-invasive treatment for paroxysmal atrial fibrillation (PAF) involving electrical nerve stimulation through an exterior part of the ear. Since Dr. Stavrakis has found that some, but not all, PAF patients see improvement given this nerve stimulation, Adeola and Dr. Hendryx are applying mathematical and statistical techniques to look for patterns in PAF patients’ electrocardiogram (ECG) data that may indicate whether a patient will actually respond to the treatment. With Dr. Stavrakis’ clinical expertise as a guide, Adeola is currently using computational algorithms to derive features from the ECG for use as model input—no small task when working with real patient data that can contain a variety of artifacts. The interdisciplinary team will continue to work on model construction over the months to come, in an effort to identify predictive ECG features and offer clinical decision support for future PAF treatment.