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Current Project: Using automatic speech recognition to transcribe audio files from patients with depression to determine efficacy of therapy. Before and after outcomes will be assessed using telephone audio files where participants were called and asked what they were “thinking” at the moments just before the call. These audio files… Read More

Our team is interested in developing natural language processing (NLP) systems using transformers to classify whether patients have drug-related adverse events from patients’ clinical notes in Vanderbilt University Medical Center electronic health records (EHRs), which could be potentially associated with a specific drug of interest. The Initial approach to this… Read More

Clinical notes and other free-text documents provide a breadth of clinical information that is not often available within structured data. Transformer-based natural language processing (NLP) models, such as BERT, have demonstrated great promise in using transfer learning to  improve clinical text processing. However, these models are commonly trained on generic corpora, which do not necessarily reflect many… Read More

As part of a larger exploration of the British Culture of Litigation (from a literary perspective), we are working on developing text-mining techniques with the corpus of Proquest British Periodicals, which contains (of its total 3.4 mil) roughly a million articles in the relevant timeframe of 1770-1850 produced in several… Read More