Statistical term profiling for query pattern mining

• Authors: Paul Buitelaar;Pinar Oezden Wennerberg;Sonja Zillner
• Venue: BioNLP '08 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
• Year: 2008

Through advanced technologies in clinical care and research, especially the rapid progress in imaging technologies, more and more medical imaging data and patient text data is generated by hospitals, pharmaceutical companies, and medical research. For enabling advanced access to clinical imaging and text data, it is relevant to know what kind of knowledge the clinician wants to know or the queries that clinicians are interested in. Through intensive interviews and discussions with radiologists and clinicians, we have learned that medical imaging data is analyzed - and hence queried -- from three different perspectives, i.e. the anatomic perspective addressing the involved body parts, the radiology-specific spatial perspective describing the relationships of located anatomical regions to other anatomical parts, and the disease perspective distinguishing between normal and abnormal imaging features. Our aim is to establish query patterns reflecting those three perspectives that would typically be used by clinicians and radiologists to find patient-specific sets of relevant images.