Extracting Temporal Constraints from Clinical Research Eligibility Criteria Using Conditional Random Fields

Temporal constraints are present in 38% of clinical research eligibility criteria and are crucial for screening patients. However, eligibility criteria are often written as free text, which is not amenable for computer processing. In this paper, we present an ontology-based approach to extracting temporal information from clinical research eligibility criteria. We generated temporal labels using a frame-based temporal ontology. We manually annotated 150 free-text eligibility criteria using the temporal labels and trained a parser using Conditional Random Fields (CRFs) to automatically extract temporal expressions from eligibility criteria. An evaluation of an additional 60 randomly selected eligibility criteria using manual review achieved an overall precision of 83%, a recall of 79%, and an F-score of 80%. We illustrate the application of temporal extraction with the use cases of question answering and free-text criteria querying.