Web-based Medical Teaching using a Multi-Agent System

Alves, Victor; Neves, José; Nelas, Luís; Marreiros, Filipe Miguel Maria

doi:10.1007/1-84628-224-1_14

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…Traditionally, medical teaching is based on texts, lectures, and bedside teaching, with self-guided individual learning based on books. 1 The traditional medical teaching and individual learning methods can be complemented with electronic learning systems delivered via the Internet, leading to the so-called e-learning paradigm. With the advancement of Web technology, e-learning has been a topic of interest in recent years and has become an important trend in medical education.…”

Section: Introductionmentioning

confidence: 99%

“…Alves et al 1 described their experience in designing a multi-agent system for e-learning in the medical area. The proposed system is based on the client/server network architecture, where the server holds the data warehouse, medical data, and the software agent that delivers medical content; on the client side, the interface is based via Internet technology.…”

Section: Introductionmentioning

confidence: 99%

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INDIAM—An e-Learning System for the Interpretation of Mammograms

et al. 2008

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We propose the design of a teaching system named Interpretation and Diagnosis of Mammograms (INDIAM) for training students in the interpretation of mammograms and diagnosis of breast cancer. The proposed system integrates an illustrated tutorial on radiology of the breast, that is, mammography, which uses education techniques to guide the user (doctors, students, or researchers) through various concepts related to the diagnosis of breast cancer. The user can obtain informative text about specific subjects, access a library of bibliographic references, and retrieve cases from a mammographic database that are similar to a query case on hand. The information of each case stored in the mammographic database includes the radiological findings, the clinical history, the lifestyle of the patient, and complementary exams. The breast cancer tutorial is linked to a module that simulates the analysis and diagnosis of a mammogram. The tutorial incorporates tools for helping the user to evaluate his or her knowledge about a specific subject by using the education system or by simulating a diagnosis with appropriate feedback in case of error. The system also makes available digital image processing tools that allow the user to draw the contour of a lesion, the contour of the breast, or identify a cluster of calcifications in a given mammogram. The contours provided by the user are submitted to the system for evaluation. The teaching system is integrated with AMDI-An Indexed Atlas of Digital Mammograms-that includes case studies, e-learning, and research systems. All the resources are accessible via the Web.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

INDIAM—An e-Learning System for the Interpretation of Mammograms

et al. 2008

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“…The last project is an e-learning-and web-based system implemented for helping in medical teaching [Alves et al 2006]. The system integrates different information sources into a common format.…”

Section: Figure 35mentioning

confidence: 99%

Agent-based management of clinical guidelines

Isern Alarcón

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Les guies de pràctica clínica (GPC) contenen un conjunt d'accions i dades que ajuden a un metge a prendre decisions sobre el diagnòstic, tractament o qualsevol altre procediment a un pacient i sobre una determinada malaltia. És conegut que l'adopció d'aquestes guies en la vida diària pot millorar l'assistència mèdica als pacients, pel fet que s'estandarditzen les pràctiques. Sistemes computeritzats que utilitzen GPC poden constituir part de sistemes d'ajut a la presa de decisions més complexos amb la finalitat de proporcionar el coneixement adequat a la persona adequada, en un format correcte i en el moment precís. L'automatització de l'execució de les GPC és el primer pas per la seva implantació en els centres mèdics. Per aconseguir aquesta implantació final, hi ha diferents passos que cal solucionar com per exemple, l'adquisició i representació de les GPC, la seva verificació formal, i finalment la seva execució. Aquesta Tesi està dirigida en l'execució de GPC i proposa la implementació d'un sistema multi-agent. En aquest sistema els diferents actors dels centres mèdics coordinen les seves activitats seguint un pla global determinat per una GPC. Un dels principals problemes de qualsevol sistema que treballa en l'àmbit mèdic és el tractament del coneixement. En aquest cas s'han hagut de tractar termes mèdics i organitzatius, que s'ha resolt amb la implementació de diferents ontologies. La separació de la representació del coneixement del seu ús és intencionada i permet que el sistema d'execució de GPC sigui fàcilment adaptable a les circumstàncies concretes dels centres, on varien el personal i els recursos disponibles. En paral·lel a l'execució de GPC, el sistema proposat manega preferències del pacient per tal d'implementar serveis adaptats al pacient. En aquesta àrea concretament, a) s'han definit un conjunt de criteris, b) aquesta informació forma part del perfil de l'usuari i serveix per ordenar les propostes que el sistema li proposa, i c) un algoritme no supervisat d'aprenentatge permet adaptar les preferències del pacient segons triï. Finalment, algunes idees d'aquesta Tesi actualment s'estan aplicant en dos projectes de recerca. Per una banda, l'execució distribuïda de GPC, i per altra banda, la representació del coneixement mèdic i organitzatiu utilitzant ontologies. Clinical guidelines (CGs) contain a set of directions or principles to assist the health care practitioner with patient care decisions about appropriate diagnostic, therapeutic, or other clinical procedures for specific clinical circumstances. It is widely accepted that the adoption of guideline-execution engines in daily practice would improve the patient care, by standardising the care procedures. Guideline-based systems can constitute part of a knowledge-based decision support system in order to deliver the right knowledge to the right people in the right form at the right time. The automation of the guideline execution process is a basic step towards its widespread use in medical centres. To achieve this general goal, different topics should be tackled, such as the acquisition of clinical guidelines, its formal verification, and finally its execution. This dissertation focuses on the execution of CGs and proposes the implementation of an agent-based platform in which the actors involved in health care coordinate their activities to perform the complex task of guideline enactment. The management of medical and organizational knowledge, and the formal representation of the CGs, are two knowledge-related topics addressed in this dissertation and tackled through the design of several application ontologies. The separation of the knowledge from its use is fully intentioned, and allows the CG execution engine to be easily customisable to different medical centres with varying personnel and resources. In parallel with the execution of CGs, the system handles citizen's preferences and uses them to implement patient-centred services. With respect this issue, the following tasks have been developed: a) definition of the user's criteria, b) use of the patient's profile to rank the alternatives presented to him, c) implementation of an unsupervised learning method to adapt dynamically and automatically the user's profile. Finally, several ideas of this dissertation are being directly applied in two ongoing funded research projects, including the agent-based execution of CGs and the ontological management of medical and organizational knowledge.

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“…Indeed, multi-agent systems have proven to be extremely scalable and offer great flexibility to the overall system design (e.g. one may point out to a multi-agent system to aid the diagnostic process [8], or a webbased medical training system [9]).…”

Section: Multi-agent Systemsmentioning

confidence: 99%

Medical Imaging Environment – A Multi-Agent System for a Computer Clustering Based Multi-display

Alves

Marreiros

Nelas³

et al.

Progress in Artificial Intelligence

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This paper presents a solution to minimize a problem that normally arises from the huge amount of images that a radiologist usually has to interpret. A multi-agent system that implements a multi-display for medical imaging based on computer clustering of normal personal computers is therefore described, as well as the multi-agent architecture that caters for the system evolution. An evaluation study was performed and its results are presented.

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Web-based Medical Teaching using a Multi-Agent System

Cited by 4 publications

References 9 publications

INDIAM—An e-Learning System for the Interpretation of Mammograms

INDIAM—An e-Learning System for the Interpretation of Mammograms

Agent-based management of clinical guidelines

Medical Imaging Environment – A Multi-Agent System for a Computer Clustering Based Multi-display

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