HermanLab Homepage
We are a computational medicine laboratory that focuses on developing, applying, and evaluating data-driven approaches to improve clinical care systems, focusing on screening for under-diagnosed diseases and cardiovascular disease diagnosis and prediction. To these ends, we are developing robust, integrative methods for analyzing clinical and other biomedical data. We are interested in both approaches that can be rapidly implemented in clinical practice and more sophisticated modeling that better leverages longitudinal, multi-dimensional patient data. We work with both existing clinical data and potential new biomarker data collected from electronic health records and epidemiologic studies. In addition, we are also developing small clinical cohorts for the evaluation of focused questions.
We are always looking for motivated individuals who are interested in using computational approaches to improve the practice of medicine. See our Opportunities page or email for more information.
Announcement
We are currently recruiting for a computational postdoctoral fellow. Click here to find out more.
News
Patient-Centered Outcomes Research Institute Methods Award
March 2021
Our proposal to develop methods for training multi-site clinical prediction models entitled "Development of Methods to Improve Identification of Patients with Rare or Complex Diseases" was funded by the Patient-Centered Outcomes Research Institute (PCORI)
Method for learning accurate and explainable EHR prediction models
February 2021
Our pre-print with Dr. Bill La Cava on training explainable EHR prediction models