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Biomedical subjects

Ioanna Chouvarda

Publications and source records attributed to Ioanna Chouvarda.

6 recordsLinked to original sources

Constructing a semantically enriched biomedical service space: a paradigm with bioinformatics resources.

Biomedical applications are becoming increasingly reliant on resource integration and information exchange within global solution frameworks that offer seamless connectivity and data sharing in distributed environments. Resource autonomy and data heterogeneity are the most important impediments towards this potential. Aiming to overcome these limitations, we propose an implementation of the service-oriented model towards the construction of an open, semantically enriched biomedical service space that enables advanced service registration, selection and access capabilities, as well as service interoperability. The proposed system is realised by defining service annotation ontologies and applying software agent technology as the means for service registration, matchmaking and interfacing in a Grid environment. The applicability of the envisioned biomedical service space is illustrated on a set of bioinformatics resources, addressing computational identification of protein-coding genes.

Computational Biology↗

A novel approach for incremental uncertainty rule generation from databases with missing values handling: application to dynamic medical databases.

Current approaches for mining association rules usually assume that the mining is performed in a static database, where the problem of missing attribute values does not practically exist. However, these assumptions are not preserved in some medical databases, like in a home care system. In this paper, a novel uncertainty rule algorithm is illustrated, namely URG-2 (Uncertainty Rule Generator), which addresses the problem of mining dynamic databases containing missing values. This algorithm requires only one pass from the initial dataset in order to generate the item set, while new metrics corresponding to the notion of Support and Confidence are used. URG-2 was evaluated over two medical databases, introducing randomly multiple missing values for each record's attribute (rate: 5-20% by 5% increments) in the initial dataset. Compared with the classical approach (records with missing values are ignored), the proposed algorithm was more robust in mining rules from datasets containing missing values. In all cases, the difference in preserving the initial rules ranged between 30% and 60% in favour of URG-2. Moreover, due to its incremental nature, URG-2 saved over 90% of the time required for thorough re-mining. Thus, the proposed algorithm can offer a preferable solution for mining in dynamic relational databases.

Algorithms↗

A multiagent system enhancing home-care health services for chronic disease management.

In this paper, a multiagent system (MAS) is presented, aiming to enhance monitoring, surveillance, and educational services of a generic medical contact center (MCC) for chronic disease management. In such a home-care scenario, a persistent need arises for efficiently monitoring the patient contacts and the MCC's functionality, in order to effectively manage and interpret the large volume of medical data collected during the patient sessions with the system, and to assess the use of MCC resources. Software agents were adopted to provide the means to accomplish such real-time information-processing tasks, due to their autonomous, reactive and/or proactive nature, and their effectiveness in dynamic environments by incorporating coordination strategies. Specifically, the objective of the MAS is to monitor the MCC environment, detect important cases, and inform the healthcare and administrative personnel via alert messages, notifications, recommendations, and reports, prompting them for actions. The main aim of this paper is to present the overall design and implementation of a proposed MAS, emphasizing its functional model and architecture, as well as on the agent interactions and the knowledge-sharing mechanism incorporated, in the context of a generic MCC.

Artificial Intelligence↗

The Citizen Health System (CHS): a modular medical contact center providing quality telemedicine services.

In the context of the Citizen Health System (CHS) project, a modular Medical Contact Center (MCC) was developed, which can be used in the monitoring, treatment, and management of chronically ill patients at home, such as diabetic or congestive heart failure patients. The virtue of the CHS contact center is that, using any type of communication and telematics technology, it is able to provide timely and preventive prompting to the patients, thus, achieving better disease management. In this paper, we present the structure of the CHS system, describing the modules that enable its flexible and extensible architecture. It is shown, through specific examples, how quality of healthcare delivery can be increased by using such a system.

Database Management Systems↗

Can P wave wavelet analysis predict atrial fibrillation after coronary artery bypass grafting?

The purpose of this study was the evaluation of Morlet wavelet analysis of the P wave as a means of predicting the development of atrial fibrillation (AF) in patients who undergo coronary artery bypass grafting (CABG). The P wave was analyzed using the Morlet wavelet in 50 patients who underwent successful CABG. Group A consisted of 17 patients, 12 men and 5 women, of mean age 66.9 +/- 5.9 years, who developed AF postoperatively. Group B consisted of 33 patients, 29 men and 4 women, mean age 62.4 +/- 7.8 years, who remained arrhythmid-free. Using custom-designed software, P wave duration and wavelet parameters expressing the mean and maximum energy of the P wave were calculated from 3-channel digital recordings derived from orthogonal ECG leads (X, Y, and Z), and the vector magnitude (VM) was determined in each of 3 frequency bands (200-160 Hz, 150-100 Hz and 90-50 Hz). Univariate logistic-regression analysis identified a history of hypertension, the mean and maximum energies in all frequency bands along the Z axis, the mean and maximum energies (expressed by the VM) in the 200-160 Hz frequency band, and the mean energy in the 150-100 Hz frequency band along the Y axis as predictors for post-CABG AF. Multivariate analysis identified hypertension, ejection fraction, and the maximum energies in the 90-50 Hz frequency band along the Z and composite-vector axes as independent predictors. This multivariate model had a sensitivity of 91% and a specificity of 65%. We conclude that the Morlet wavelet analysis of the P wave is a very sensitive method of identifying patients who are likely to develop AF after CABG. The occurrence of post-CABG AF can be explained by a different activation pattern along the Z axis.

Aged↗

Agent-based monitoring and alert generation for a home care telemedicine system.

In the present paper, a multi-agent system is proposed, which can be integrated in the home care telemedicine system that was developed in the context of the Citizen Health System (CHS) European project, functioning as a contact center for diabetic and congestive heart failure patients. The objective of the multi-agent system is to provide a set of alert/notification mechanisms for the clinicians, helping them to classify the clinical condition of each patient. Therefore, despite the huge amount of data managed by the system, due to the daily use of the contact center's services, these alert mechanisms provide the clinician with an overview of the cases that need further examination and save him/her time from the trivial cases. The multi-agent system consists of different types of agents, each one assigned with specific tasks, which communicate with each other, in order to share knowledge.

Computer Systems↗