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Gianluca Correndo

Publications and source records attributed to Gianluca Correndo.

3 recordsLinked to original sources

A context-adaptable approach to clinical guidelines.

One of the most relevant obstacles to the use and dissemination of clinical guidelines is the gap between the generality of guidelines (as defined, e.g., by physicians' committees) and the peculiarities of the specific context of application. In particular, general guidelines do not take into account the fact that the tools needed for laboratory and instrumental investigations might be unavailable at a given hospital. Moreover, computer-based guideline managers must also be integrated with the Hospital Information System (HIS), and usually different DBMS are adopted by different hospitals. The GLARE (Guideline Acquisition, Representation and Execution) system addresses these issues by providing a facility for automatic resource-based adaptation of guidelines to the specific context of application, and by providing a modular architecture in which only limited and well-localised changes are needed to integrate the system with the HIS at hand.

Computer Graphics↗

Towards a flexible integration of clinical guideline systems with medical ontologies and medical information systems.

The integration of a computer-based system dealing with clinical guidelines with a medical ontology can provide several advantages, including standardization and knowledge sharing. Furthermore, in order to operate in the clinical practice, guideline systems must also interact with the hospital databases to retrieve patients' data. Unfortunately, currently there seems not to be any "standard" consensus model either for the medical ontology or for (the conceptual structure of) patient databases (even if several interesting proposals have been carried out). In this paper we show how we are extending the GLARE guideline manager in order to strictly interact with both a medical ontology and a patient Database, in such a way that GLARE is not committed to any specific ontology and database (i.e., different ontologies and/or databases can be used).

Humans↗

The GLARE approach to clinical guidelines: main features.

In this paper, we present GLARE, a domain-independent prototypical system for acquiring, representing and executing clinical guidelines. GLARE has been built within a 7-year project with Azienda Ospedaliera San Giovanni Battista in Turin (one of the largest hospitals in Italy) and has been successfully tested on clinical guidelines in different domains, including bladder cancer, reflux esophagitis, and heart failure. GLARE is characterized by the adoption of advanced Artificial Intelligence (AI) techniques, to support medical decision making and to manage temporal knowledge.

Decision Making, Computer-Assisted↗