Automated linkage of free-text descriptions of patients with a practice guideline.
Year: 1993
Type: article
Abstract: The process of applying a practice guideline to a patient requires a great deal of clinical data. AAPT (Appropriateness-Assessment Processing from Text) is an experimental computer program that can assess the appropriateness of coronary-artery bypass grafting surgery (CABG) in patients with coronary-artery disease (CAD) and chronic stable angina from the admission summaries of those patients. The AAPT architecture combines natural-language processing (NLP) and probabilistic inference. The NLP module identifies single clinical concepts of interest in the free-text document. The probabilistic inference module, a Bayesian belief network, estimates values for variables not specifically mentioned. AAPT produces a patient's summary of CAD that is similar to a manually generated clinical summary. Work is ongoing to improve AAPT and evaluate it as a tool to assist in the dissemination of guidelines and as a tool to encourage adherence to practice guidelines.
Source: PubMed Central
Authors: L A Lenert, M Tovar
Institutions: Stanford Medicine, Stanford University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W1445338536