CIQR enables clinicians working in the field to pose questions in natural language and receive responses, without interrupting their workflow.
During the process of patient care, clinicians frequently experience the need for information about treatment, diagnostic workup, disease progression and other aspects of patient management. In most of these situations, it is difficult or impossible for the clinician to immediately access appropriate information resources. Most information needs are never adequately articulated or recorded, and consequently are forgotten by the end of the day. Moreover, when clinicians do recall information needs, they often don't act on them, due to the significant limitations of current retrieval systems and the exigencies of clinical practice.
CIQR is the outgrowth of several years of research in information retrieval with the goal of finding out what information the user really wants to know and delivering it when and where it is needed. A unique aspect of the approach is that the user submits open-ended, multi-sentence questions, not just key words. This enables the user to provide contextual background related to the question, such as pertinent characteristics of the patient, the purpose of the query, and the kind of materials the user is seeking. These items provide vital clues for constructing search strategies that are better tuned to the user's environment and emergent goals.
| Eneida Mendonca | Principal Investigator |
| Stephen Johnson | Investigator |
| David Kaufman | Investigator |
| Peter Hung | Fellow |
| Sarah Gilman | Masters Student |
| Dan Langsam | Visiting Student |
| Randi Jorgensen | Visiting Student |
| Jacob Melgaard | Visiting Student |
Tuesdays 10:00-11:00am, Vanderbilt Clinic, 5th Floor, Conference Room B
You can post messages to ciqr atsign dbmi. Please send mail to Professor Mendonca if you would like to be added to this list.