End-End Systems

Temporal History of Your Medical Events (THYME)

*** The THYME project is a joint project between the Mayo Clinic, the Children's Hospital Boston and the University of Colorado Boulder. It is funded by the NIH. ***

The ever increasing amounts of electronic clinical data calls for technologies that can enable efficient indexing, retrieval and data mining. One of the most crucial components of such a system is a means of discovering events and their relations on a timeline. Temporal relations are of prime importance in biomedicine as they are intrinsically linked to diseases, signs and symptoms, and treatments. Understanding the timeline of clinically relevant events is key to the next generation of translational research where the importance of generalizing over large amounts of data holds the promise of deciphering biomedical puzzles.

The goal of the current research is to discover temporal relations from clinical free text through achieving four specific aims:

Specific Aim 1: Develop (1) a temporal relation annotation schema and guidelines for clinical free text based on TimeML, which will require extensions to Treebank, PropBank and VerbNet annotation guidelines to the clinical domain, (2) an annotated corpus following the temporal relations schema with additions to Treebank, PropBank and VerbNet, (3) a descriptive study comparing temporal relations in the clinical and general domains.

Specific Aim 2: Extend and evaluate existing methods and/or develop new algorithms for temporal relation discovery in the clinical domain.

Specific Aim 3: Integrate best method and/or a variety of methods for temporal relation discovery into the open source Mayo Clinic Information Extraction pipeline (cTAKES) and release as open source annotators for the larger community to use and contribute to.

Specific Aim 4: System-level evaluation. Test the functionality of the enhanced Mayo Clinic IE pipeline on translational research use cases, e.g. the progression of colon cancer as documented in clinical notes and pathology reports, the progression of brain tumor as documented in radiology reports.

The following annotation guidelines are being developed, used and adpated to clinical text in this project:
THYME Annotation Guidelines
Syntactic tree (TreeBank) annotation guidelines
Semantic role (PropBank) annotation guidelines
Unified Medical Language System (UMLS) entity annnotation guidelines
Clinical coreference annnotation guidelines