Research in Dr. Das’s lab focuses on technological innovations for acquiring, applying and mining structured and axiomatic knowledge, particularly in the form of the Semantic Web standards OWL and SWRL. Although our approach is domain independent, our informatics work is motivated by the needs of clinicians and clinical researchers who capture and share knowledge through collaborative efforts, such as in comparative effectiveness research, clinical trials management, and disease phenotype characterization. Our semantic computing methods can enable both people and computers to rapidly and intelligently make sense of complex clinical information, such as longitudinal data, clinical protocols, and rule bases.
Highlights of our recent work include:
Temporal mining methods that discover temporal associations between new mutations and past treatments in HIV drug resistance and that perform temporal clustering of patient cohorts based on similar histories of breast cancer care.
Semantic integration methods that can acquire knowledge about biomedical concepts encoded in CSV spreadsheets and that can allow XML-driven specification of clinical trial software.
Rule management methods that support predictive rule editing for acquiring definitions of autism phenotypes and that allow visualization of logical dependencies among rules on family health history.
Intelligent user interface methods that support question answering of online resources on HIV drug resistance and that enable Web-based exploration of temporal data for comparative effectiveness research.