Biomedical subjects

S Falasconi

Publications and source records attributed to S Falasconi.

6 recordsLinked to original sources

PubMed1999

A framework for building cooperative software agents in medical applications.

Exploiting the information technology may have a great impact on improving cooperation and interoperability among the different professionals taking part to the process of delivering health care services. New paradigms are therefore being devised considering software systems as autonomous agents able to help professionals in accomplishing their duties. To this aim those systems should encapsulate the skills for solving a given set of tasks and possess the social ability to cooperate in order to fetch the required information and knowledge. This paper illustrates a methodology facilitating the development of interoperable intelligent software agents for medical applications and proposes a generic computational model for implementing them. That model may be specialized in order to support all the different information and knowledge related requirements of a Hospital Information System. The architecture is being tested for implementing a prototype system able to coordinate the joint efforts of the professionals involved in managing patients affected by Acute Myeloid Leukemia.

Computer Simulation↗

PubMed1998

Organizational & medical ontologies for co-operative patient management.

A new research paradigm is emerging based on the Multi-Agent System (MAS) architectural framework, allowing human and software agents to interoperate and thus cooperate within common application areas. In this paper, we discuss an ontological foundation for a prototypical health care MAS, that is, a so-called Distributed Healthcare Information System (D-HIS), viewed as an organization of cognitive agents and making use of an ontological library written in the standard language Ontolingua.

Computer Communication Networks↗

PubMed1998

Towards cooperative patient management through organizational and medical ontologies.

Within knowledge and data engineering a new research paradigm is emerging based on the Multi-Agent System (MAS) architectural framework, allowing human and software agents to interoperate and thus cooperate within common application areas. In such a framework, knowledgeable agents of heterogeneous nature, that possess diverse but at least partially compatible or inter-translatable conceptual views, or ontologies, modeling both their own expertise and the external environment, make somehow available their information resources or problem-solving abilities for cooperative processes addressing the construction of a new agent or the achievement of some common goal through a correlated execution of tasks. In this paper, we restrict our analysis to the case of an organization of cognitive agents, illustrated with examples from a prototypical healthcare MAS, that is, a so-called Distributed Healthcare Information System (D-HIS). The prototype makes use of an ontological library written in the standard language Ontolingua. An ongoing application of the methodology to the main problem of Clinical Practice Guidelines (GLs) computer-based dissemination and enforcement is described.

Artificial Intelligence↗

PubMed1997

An ontology-based multi-agent architecture for distributed health-care information systems.

Managing patients in a shared-care context is a knowledge-intensive activity. To support cooperative work in medical care, computer technology should both augment the capabilities of individual specialists and enhance their ability of interacting with each other and with computational resources. Thus, a major shift is needed from centralized first generation health-care information systems to distributed environments composed of several interconnected agents, cooperating in maintaining a full track of the patient clinical history and supporting health-care providers in all the phases of the patient-management process. This paper outlines a general methodology to make architectural choices while designing or integrating new software components into a distributed health-care information system. A particular stress is laid on the specification of shared conceptual models, or ontologies, providing agents committing to them with the common semantic foundation required for effective interoperation.

Computer Communication Networks↗

PubMed1997

Ontology and terminology servers in agent-based health-care information systems.

A new research paradigm is emerging based on the multi-agent system architectural framework, allowing human and software agents to interoperate and thus cooperate within common application areas. Within a multi-agent system, the different "views of the world" of knowledgeable agents are to be bridged through their commitment to common ontologies and terminologies. We developed a general methodology for the design or integration of new components into a Health-care Information System conceived as a network of software and human agents. In our view, ontological and terminological services are entrusted to dedicated agents, namely ontology and terminology servers, allowing the configuration of suitable application ontologies for distributed applications. The role is described that such servers, operatively coordinated in order to preserve semantic coherence, should play within a distributed Health-care Information System.

Computer Communication Networks↗

PubMed1995

A case study in ontology library construction.

The goal of our work is to facilitate the development of medical knowledge-based systems by providing a library of reusable ontologies. The availability of such a library reduces the amount of knowledge acquisition required to create knowledge bases of new applications, and makes it easier to connect a knowledge-based system to existing data bases. This article presents a case study in constructing such a library. The emphasis is on studying the principles that underly the internal structure of the library as well as on the process of constructing and using the library. We envision that, in the future, application ontologies can be constructed by the selection and refinement of generic ontologies and domain ontologies from such a library.

Artificial Intelligence↗