The Gonzalez-Hernandez Health Language Processing Laboratory aims to improve healthcare delivery and public health surveillance through innovations in automated language processing. Working with clinicians, epidemiologists and other domain experts, our laboratory brings internationally recognized experts in natural language processing, machine learning, and artificial intelligence to develop and deploy innovative, scalable solutions for the systematic mining of free text in real-world data (such as medical records, published literature and user-generated content). We promote open, reproducible research in health language processing through publications in high impact journals that includes annotated data sets and open-source code or models, and through the organization of workshops and shared tasks.
Our domains of interest include, but are not limited to:
- Published medical literature (e.g., articles from PubMed Central)
- Social media (e.g., Twitter posts)
- Medical records (e.g., patient notes)
Our goals include:
- Developing innovative NLP solutions for health-related language
- Creating data, resources and tools for the global research community
- Promoting research in health language processing through the organization of workshops and shared tasks, and through interdisciplinary collaborations
We are always interested in interesting health-related language processing problems. Contact us if you have one!