Integration of Temporal Abstraction and Dynamic Bayesian Networks in Clinical Systems. A preliminary approach

Abstraction of temporal data (TA) aims to abstract time-points into higher-level interval concepts and to detect significant trends in both low-level data and abstract concepts. TA methods are used for summarizing and interpreting clinical data. Dynamic Bayesian Networks (DBNs) are temporal probabilistic graphical models which can be used to represent knowledge about uncertain temporal relationships between events and state changes during time. In clinical systems, they were introduced to encode and use the domain knowledge acquired from human experts to perform decision support. A hypothesis that this study plans to investigate is whether temporal abstraction methods can be effectively integrated with DBNs in the context of medical decision-support systems. A preliminary approach is presented where a DBN model is constructed for prognosis of the risk for coronary artery disease (CAD) based on its risk factors and using as test bed a dataset that was collected after monitoring patients who had positive history of cardiovascular disease. The technical objectives of this study are to examine how DBNs will represent the abstracted data in order to construct the prognostic model and whether the retrieved rules from the model can be used for generating more complex abstractions

Embedding Quality Culture in Higher Education Provision

As a result of the Bologna Process and other global developments in the area of higher education, the issue of quality has acquired key significance. Higher education institutions are called upon to embed quality culture in their education provision. This would enhance the trust societies put on them, make them more accountable, and result in higher autonomy for them. This paper focuses on the quality management of educational programmes in view of European and global developments in higher education and suggests various quality indicators. It is argued that embedding quality culture is necessary for safeguarding against minimum quality standards for academic and professional qualifications. It is also argued that quality, particularly with respect to higher education provision, is multi-dimensional, thus reducing or abstracting it to a single figure, as it happens with ranking systems, is unduly simplistic, can hide important information, and could be misrepresentative of the true situation, both in a positive or negative way. As a test case, the author describes the quality scene for higher education in Cyprus

Case Based Representation and Retrieval with Time Dependent Features

Abstract. The temporal dimension of the knowledge embedded in cases has often been neglected or oversimplified in Case Based Reasoning sys-tems. However, in several real world problems a case should capture the evolution of the observed phenomenon over time. To this end, we propose to represent temporal information at two levels: (1) at the case level, if some features describe parameters varying within a period of time (which corresponds to the case duration), and are therefore collected in the form of time series; (2) at the history level, if the evolution of the system can be reconstructed by retrieving temporally related cases. In this paper, we describe a framework for case representation and retrieval able to take into account the temporal dimension, and meant to be used in any time dependent domain. In particular, to support case retrieval, we provide an analysis of similarity-based time series retrieval techniques; to support history retrieval, we introduce possible ways to summarize the case content, together with the corresponding strategies for identifying similar instances in the knowledge base. A concrete ap-plication of our framework is represented by the system RHENE, which is briefly sketched here, and extensively described in [20].

Temporal diagnostic reasoning based on time-objects

Time is essential in diagnostic problem-solving. However, as with other commonsense tasks, time representation and reasoning is not a trivial undertaking. This probably explains why time has either been ignored or implicitly represented and used in the majority of diagnostic systems, medical or otherwise. Durations, temporal uncertainty and multiple temporal granularities are necessary requirements for medical problem-solving. Most general theories of time proposed in the literature do not address all these requirements, and some do not address any. The paper discusses time representation and reasoning in medical diagnostic problem-solving, building from a generic temporal ontology which covers the above temporal requirements. Much of what is discussed, however, is applicable to non-medical domains as well. It is argued that the diagnostic concepts (patient data, disorders, therapeutic-actions) are naturally modelled as time-objects. The resulting representation treats time as an integral dimension to these concepts, with special status. Time-object-based representations for generic hypotheses (disorders, actions) are discussed and illustrated; in the case of disorders the representation covers both an associational model and a causal-associational model. A central function of diagnostic problem-solving is deciding the compatibility of hypotheses with regard to a patient model. In this respect the paper discusses temporal and contextual screening of triggered hypotheses as well as accountings and conflicts between time-object

Temporal constraints in clinical diagnosis

Time representation and temporal reasoning are of crucial importance to clinical diagnosis. In this paper we present a general model for diagnostic knowledge, the Causal-Temporal-Action (C-T-A) model. This has a central tri-planar structure for the representation, in causal terms, of knowledge on disorders and physiological processes. The central structure is bounded by two other, orthogonal planes that represent temporal constraints and therapeutic actions. These planes function to constrain the existences of the temporal entities residing on the central structure. A major focus of the paper is the temporal constraints plane of the C-T-A model. An abstract structure, the Abstract Temporal Graph (ATG) is proposed for the representation of temporal constraints. Specific cases of the ATG structure encountered in the literature on temporal clinical diagnosis are discussed and algorithms for checking the consistency and satisfiability of temporal constraints are presented. These algorithms are of relevance to the validation of diagnostic knowledge and patient data and the evaluation of diagnostic hypothese

Multidimensional and multigranular model of time for medical knowledge-based systems

In temporal reasoning there are two interrelated issues; how to model time per se and how to model occurrences. In medical temporal reasoning the need for multiple granularities and multiple conceptual temporal contexts arises in relation to a model of time. Some occurrence can then be expressed with respect to different temporal contexts. This paper presents a multidimensional and multigranular model of time for knowledge-based problem solving, primarily for medical applications. Both the conceptual issues and the design issues underlying the implementation of the proposed model are discussed. The presented model of time has been developed in the context of a time ontology for medical knowledge engineering, whose principal primitives are the time-axis and the time-object. The notion of a time-axis constitutes the primitive for the proposed model of time, while the notion of a time-object aims to integrate time with other essential forms of knowledge, such as structural and causal knowledge, in the expression of different types of occurrences, thus resulting in the integral embodiment of time in such occurrences. The notion of a time-object and the overall ontology of occurrences is given only a cursory mention in this paper. The focus of the paper is the time model. More specifically, the paper presents the notion of a time-axis in the context of the overall time ontology and discusses at length the two classes of time-axes, namely the atomic axes and the spanning axes. The assertion language which has been developed, for the entire ontology, for the expression of axioms (deductive rules and integrity constraints), attribute constraints and propagation methods is presented and illustrated. The implementation of the time model in terms of a layered object-based system is also presente