187,759 research outputs found
Supporting the distributed execution of clinical guidelines by multiple agents
No full textClinical guidelines (GLs) are widely adopted in order to improve the quality of patient care, and to optimize it. To achieve such goals, their application on a specific patient usually requires the interventions of different agents, with different roles (e.g., physician, nurse), abilities (e.g., specialist in the treatment of alcohol-related problems) and contexts (e.g., many chronic patients may be treated at home). Additionally, the responsibility of the application of a guideline to a patient is usually retained by a physician, but delegation of responsibility (of the whole guideline, or of a part of it) is often used
equired (e.g., delegation to a specialist), as well as the possibility, for a responsible, to select the executor of an action (e.g., a physician may retain the responsibility of an action, but delegate to a nurse its execution). To manage such phenomena, proper support to agent interaction and communication must be provided, providing agents with facilities for (1) treatment continuity (2) contextualization, (3) responsibility assignment and delegation (4) check of agent “appropriateness”. In this paper we extend GLARE, a computerized GL management system, to support such needs. We illustrate our approach by means of a practical case study
Carbon balance gradient in European forests: should we doubt 'surprising' results? A reply to Piovesan & Adams
No full textThis paper responds to the Forum contribution by Piovesan & Adams (2000) who criticized the results obtained by the EUROFLUX network on carbon fluxes of several European forests. The major point of criticism was that the data provided by EUROFLUX are inconsistent with current scientific understanding. It is argued that understanding the terrestrial global carbon cycle requires more than simply restating what was known previously, and that Piovesan & Adams have not been able to show any major conflicts between our findings and ecosystem or atmospheric-transport theories
A constraint-based approach for the conciliation of clinical guidelines
No full textThe medical domain often arises new challenges to Artificial Intelligence. An emerging challenge is the support for the treatment of patients affected by multiple pathologies (comorbid patients). In the medical context, clinical practice guidelines (CPGs) are usually adopted to provide physicians with evidence-based recommendations, considering only single pathologies. To support physicians in the treatment of comorbid patients, suitable methodologies must be devised to “merge” CPGs. Techniques like replanning or scheduling, traditionally adopted in AI to “merge” plans, must be extended and adapted to fit the requirements of the medical domain. In this paper, we propose a novel methodology, that we term “conciliation”, to merge multiple CPGs, supporting the treatments of comorbid patients
Dealing with temporal indeterminacy in relational databases: An AI methodology
No full textTime is pervasive of the human way of approaching reality, so that it has been widely studied in many research areas, including AI and relational Temporal Databases (TDB). While temporally imprecise information has been widely studied by the AI community, only few approaches have faced temporal indeterminacy (in particular, “don’t know exactly when” indeterminacy) in TDBs. Indeed, as we will show in this paper, the treatment of time in general, and of temporal indeterminacy in particular, involves the introduction of implicit forms of data representation in TDBs. As a consequence, we propose a new AI -style methodology to cope with temporal indeterminacy in TDBs. Specifically, we show that typical AI notions and techniques, such as making explicit the semantics of the representation formalism, and adopting symbolic manipulation techniques based on such a semantics, can be fruitfully exploited in the development of a “principled ” treatment of indeterminate time in relational databases
Supporting Physicians in the Detection of the Interactions between Treatments of Co-Morbid Patients
No full textThe treatment of patients affected by multiple diseases (comorbid patients) is one of the main challenges for modern healthcare. Clinical practice guidelines are widely used to support physicians, providing them evidence-based information of interventions, but only on individual pathologies. This sets up the urgent need of developing methodologies to support physicians in the detection of interactions between guidelines, to help them in the treatment of comorbid patients. In this chapter, the authors identify different levels of abstractions in the analysis of interactions, based on both the hierarchical organization of clinical guidelines (in which composite actions are refined into their components) and the hierarchy of drug categories. They then propose a general methodology (data/knowledge structures and reasoning algorithms operating on them) supporting user-driven and flexible interaction detection over multiple levels of abstraction.No Full Tex
Oltre il multiculturalismo : retoriche e realtà delle politiche di integrazione degli immigrati
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Coping with “Exceptional” Patients in META-GLARE
No full textMany different computer-assisted management systems for Computer Interpretable Guidelines (CIGs) have been developed. While CIGs propose evidence-based treatments of “typical” patients, exceptions may arise, as well the need to cope with comorbidities. Though the treatment of both phenomena involves a deviation from the “standard” execution of CIGs, until now they have been managed as different problems, and no homogeneous approach to cope with both of them has been devised. In this paper we present the extensions to META-GLARE to overcome such a limitation. To achieve such a goal, we propose a modular architecture supporting the concurrent execution of multiple guidelines, integrated with an ontological knowledge base and with several reasoning mechanisms, including temporal reasoning and goal-based planning.No Full Tex
Conformance analysis for comorbid patients in Answer Set Programming
No full textThe treatment of comorbid patients is a hot problem in Medical Informatics, since the plain application of multiple Computer-Interpretable Guidelines (CIGs) can lead to interactions that are potentially dangerous for the patients. The specialized literature has mostly focused on the “a priori” or “execution-time” analysis of the interactions between multiple Computer-Interpretable Guidelines (CIGs), and/or CIG “merge”. In this paper, we face a complementary problem, namely, the a posteriori analysis of the treatment of comorbid patients. Given the CIGs, the history of the status of the patient, and the log of the clinical actions executed on her, we try to explain the actions executed on the patient (i.e., the log) in terms of the actions recommended by the CIGs, of their potential interactions, and of the possible ways of managing each such interaction, pointing out (i) deviations from CIG recommendations not explained in terms of interaction management (if any) and (ii) unmanaged interactions (if any). Our approach is based on Answer Set Programming, and, to face realistic problems, devotes specific attention to the temporal dimension
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