The section of Medical Informatics conducts multiple lines of research to facilitate the access of clinical information in free text for clinical and translational research.
The section's focus areas include the following:
- Incorporating natural language processing (NLP) into clinical data warehouse. Leveraging big data technologies, researchers in the section of Medical Informatics establish real-time NLP infrastructures on clinical data.
- Enabling customizable information extraction. Utilizing the latest advances in natural language processing, the section develops NLP infrastructures that allow subject matter experts to develop and execute phenotyping algorithms.
- Bring natural language processing to the point of preventive care. After section of Medical Informatics researchers tailor natural language processing to specific subdomains, the section's researchers create NLP systems that achieve almost perfect performance in information extraction to enable decision-making support at the point of preventive care.
- Normalizing, integrating and summarizing clinical data. Research in this area is aimed at normalizing and integrating information about clinical data.
- Summarizing knowledge to answer clinical questions. Research in this area is aimed at providing health sciences investigators and clinicians with relevant documents and summarization to advance the practice of evidence-based medicine.