I am interested in computer modelling of clinical decision making. This work involves understanding how clinicians make decisions and produce computer applications that can support this process.

My research explores and develops new approaches to increase the model fidelity of clinical decision making and to enhance the fluency and interactivity of the clinical knowledge management and decision support systems. I accomplish this using mathematical and statistical principles of knowledge representation, decision making, pattern recognition and planning in artificial intelligence. This enables not only the understanding on the processes involved but their efficient implementation on computers. I strive for the mathematical rigour of my work with emphasis both on strong mathematical foundations and on careful realization in efficient and robust algorithms.

Currently my main application area is computerisation of clinical practice guidelines. In this area I had the opportunity to contribute to the successful implementation of MATE, a clinical guideline-based decision support system for breast cancer multidisciplinary meeting. I was principal software developer and continue providing support to this project.

Overseeing the implementation of the systems in real settings leads me to possess a reasonable command of medical informatics standards such as HL7, EN13606 and DICOM, to which I try to contribute from the perspective of what is required for decision making (representation, traceability, etc.). This practical work makes me aware of the implementation constrains over such systems.

I have always been fascinated by the clinical diagnosis potential of magnetic resonance imaging and spectroscopy, and therefore I devote myself to understand the physical principles of magnetism,  the signal and image processing problems, and the image interpretation challenges so that more accurate and versatile decision support systems based on this technology could be implemented.

Keywords:  clinical decision support systems, statistical decision theory, pattern recognition, medical imaging, signal processing, biomedical computing and discrete mathematics.