Research Interests: I am interested in novel computational discovery methods to support biomedical research and clinical decision support systems. I apply knowledge discovery and data mining (KDD), literature based discovery (LBD), formal languages and inference to create tools that support scientific discovery.
My research focuses on how information systems can improve evidence based medicine (EBM) using intelligent algorithms that automate cognitive tasks such as evidence synthesis - drawing a uniform set of conclusions from several clinical trials. Systematic reviews are a critical component of EBM yet 80% are never updated and most are incomplete. The systematic review process can take between 1 and 2 years. The aim of the research is to simplify the tasks undertaken by systematic reviewers through automation. I achieve this aim through innovative research into algorithms, interfaces and tools that accelerate and improve the review process.
In addition I research the identification of appropriate clinical quality indicators to better answer the question of how to measure quality of care efficiently, accurately and often.
In bioinformatics my research is in DNA sequence modelling using formal languages, with a focus on the genetic mechanisms bacteria use to rapidly evolve resistance to antibiotics.
Broad Research Areas:
Clinical Decision Support Systems, Automation of Evidence Based Medicine, Translational Bioinformatics, Genome Analysis, Cancer, Antibiotic Resistance
Society Memberships & Professional Activities:
American Medical Informatics Association (AMIA), American Association for the Advancement of Science (AAAS), International Society for Computational Biology (ISCB)
Specific Research Keywords:
Bioinformatics, Translational Research, Computational Discovery, Decision Support Systems, Antibacterial Drug Resistance, Cancer, Epigenetics, Formal Languages, Machine Learning, Literature Based Discovery