Information extraction from clinical trials

Evidence-based medicine (EBM) stipulates that decisions regarding the effectiveness of potential interventions should be based on objective evidence such as randomized clinical trials and systematic reviews. However, research output rate is accelerating faster than it is feasible to manually synthesize into summaries, clinical practice guidelines and other decision aids. The most likely solution lies in the computerized summarization of this research. In this thesis we perform an extensive systematic literature review regarding methods of extracting information targets from clinical trials. Based on this review, we select a method to be analysed and the experiment to be re-produced and critically appraised. Upon successful recreation of the experiment, we annotate a new corpus consented upon by two annotators. We run the experiment on the new corpus and compare the extraction results. Finally, we present two methods to possibly advance the difficult task of extracting key information elements from clinical trials.