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Decision Support Systems, Clinical

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Using Semantic Components to Represent Dynamics of an Interdisciplinary Healthcare Team in a Multi-Agent Decision Support System.

Journal of medical systems
In healthcare organizations, clinical workflows are executed by interdisciplinary healthcare teams (IHTs) that operate in ways that are difficult to manage. Responding to a need to support such teams, we designed and developed the MET4 multi-agent sy...

Predicting Health Care Utilization After Behavioral Health Referral Using Natural Language Processing and Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Mental health problems are an independent predictor of increased healthcare utilization. We created random forest classifiers for predicting two outcomes following a patient's first behavioral health encounter: decreased utilization by any amount (AU...

Characterization of the Context of Drug Concepts in Research Protocols: An Empiric Study to Guide Ontology Development.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We examined a large body of research study documents (protocols) to identify mentions of drug concepts and established base concepts and roles needed to characterize the semantics of these instances. We found these concepts in three general situation...

Data-driven knowledge acquisition, validation, and transformation into HL7 Arden Syntax.

Artificial intelligence in medicine
OBJECTIVE: The objective of this study is to help a team of physicians and knowledge engineers acquire clinical knowledge from existing practices datasets for treatment of head and neck cancer, to validate the knowledge against published guidelines, ...

Assessing the feasibility of a mobile health-supported clinical decision support system for nutritional triage in oncology outpatients using Arden Syntax.

Artificial intelligence in medicine
BACKGROUND: Nutritional screening procedures followed by regular nutrition monitoring for oncological outpatients are no standard practice in many European hospital wards and outpatient settings. As a result, early signs of malnutrition are missed an...

Using Arden Syntax for the creation of a multi-patient surveillance dashboard.

Artificial intelligence in medicine
OBJECTIVE: Most practically deployed Arden-Syntax-based clinical decision support (CDS) modules process data from individual patients. The specification of Arden Syntax, however, would in principle also support multi-patient CDS. The patient data man...

Real alerts and artifact classification in archived multi-signal vital sign monitoring data: implications for mining big data.

Journal of clinical monitoring and computing
Huge hospital information system databases can be mined for knowledge discovery and decision support, but artifact in stored non-invasive vital sign (VS) high-frequency data streams limits its use. We used machine-learning (ML) algorithms trained on ...

Pediatric decision support using adapted Arden Syntax.

Artificial intelligence in medicine
BACKGROUND: Pediatric guidelines based care is often overlooked because of the constraints of a typical office visit and the sheer number of guidelines that may exist for a patient's visit. In response to this problem, in 2004 we developed a pediatri...