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Biomedical subjects

Carlo Combi

Publications and source records attributed to Carlo Combi.

3 recordsLinked to original sources

Temporal representation and reasoning in medicine: Research directions and challenges.

OBJECTIVE: The main aim of this paper is to propose and discuss promising directions of research in the field of temporal representation and reasoning in medicine, taking into account the recent scientific literature and challenging issues of current interest as viewed from the different research perspectives of the authors of the paper. BACKGROUND: Temporal representation and reasoning in medicine is a well-known field of research in the medical as well as computer science community. It encompasses several topics, such as summarizing data from temporal clinical databases, reasoning on temporal clinical data for therapeutic assessments, and modeling uncertainty in clinical knowledge and data. It is also related to several medical tasks, such as monitoring intensive care patients, providing treatments for chronic patients, as well as planning and scheduling clinical routine activities within complex healthcare organizations. METHODOLOGY: The authors jointly identified significant research areas based on their importance as for temporal representation and reasoning issues; the subjects were considered to be promising topics of future activity. Every subject was addressed in detail by one or two authors and then discussed with the entire team to achieve a consensus about future fields of research. RESULTS: We identified and focused on four research areas, namely (i) fuzzy logic, time, and medicine, (ii) temporal reasoning and data mining, (iii) health information systems, business processes, and time, and (iv) temporal clinical databases. For every area, we first highlighted a few basic notions that would permit any reader--including those who are unfamiliar with the topic--to understand the main goals. We then discuss interesting and promising directions of research, taking into account the recent literature and underlining the yet unresolved medical/clinical issues that deserve further scientific investigation. The considered research areas are by no means disjointed, because they share common theoretical and methodological features. Moreover, subjects of imminent interest in medicine are represented in many of the fields considered. CONCLUSIONS: We propose and discuss promising subjects of future research that deserve investigation to develop software systems that will properly manage the multifaceted temporal aspects of information and knowledge encountered by physicians during their clinical work. As the subjects of research have resulted from merging the different perspectives of the authors involved in this study, we hope the paper will succeed in stimulating discussion and multidisciplinary work in the described fields of research.

Artificial Intelligence↗

Merging multimedia presentations and semistructured temporal data: a graph-based model and its application to clinical information.

OBJECTIVE: In this paper, we focus on the issue of providing physicians with the capability of representing in a seamless way both temporal aspects of multimedia semistructured data and their temporal presentation requirements. BACKGROUND: Semistructured data are data having some structure, that may be irregular or incomplete and does not necessarily conform to a fixed schema. Semistructured data often contain the description of histories of the considered real world. The eXtensible Markup Language (XML) is becoming a cross compatible and standardized means for representing semistructured clinical data. In the field of medical informatics, there are many ongoing activities concerning XML. In the field of multimedia database systems, the topic related to the integration of several media objects (with their temporal aspects) have been considered both for data modeling and querying issues and for modeling multimedia presentations. METHODOLOGY: We first propose the Multimedia Temporal Graphical Model (MTGM), by representing a clinical database for cardiology patients undergoing cardiac angiographies and then describe it in a formal way. We deal with the problem of expressing MTGM data by XML and of managing MTGM clinical data through an XML-based system. We provide both a technique for translating (a part of) an MTGM database into an XML document and some techniques allowing us to obtain presentations defined by means of the Synchronized Multimedia Integration Language (SMIL) from MTGM presentations. RESULTS: MTGM allows one to represent and store clinical information in a semistructured, temporal, and multimedia database. The physician can define multimedia presentations based on the stored data. Multimedia presentations are then stored in the same MTGM database together with temporal clinical information and are thus represented according to the same data model. A prototype based on an XML native database system has been designed and implemented. DISCUSSION AND CONCLUSIONS: In this work we have considered the theoretical and methodological issues concerning the definition of a general data model for describing temporal and multimedia features of semistructured clinical information. Other research and application oriented features, which have not been considered in MTGM, could be investigated for completing MTGM with regard to its applicability to clinical domains: MTGM does not allow one to express times at different levels of granularities, i.e. with different time units, or with indeterminacy; besides the considered valid time, it could be interesting to manage also other temporal dimensions such as the transaction and availability times. Besides being useful for managing multimedia data stored according to widely accepted standards as MPEG and DICOM, nowadays semistructured data, and XML in particular, are becoming the most important way for expressing and exchanging medical knowledge and data: MTGM can be considered as a data model allowing the seamless representation of both (multimedia and temporal) clinical data and knowledge.

Artificial Intelligence↗

User-oriented views in health care information systems.

In this paper, we present the methodology we adopted in designing and developing an object-oriented database system for the management of medical records. The designed system provides technical solutions to important requirements of most clinical information systems, such as 1) the support of tools to create and manage views on data and view schemas, offering to different users specific perspectives on data tailored to their needs; 2) the capability to handle in a suitable way the temporal aspects related to clinical information; and 3) the effective integration of multimedia data. Remote data access for authorized users is also considered. As clinical application, we describe here the prototype of a user-oriented clinical information system for the archiving and the management of multimedia and temporally oriented clinical data related to percutaneous transluminal coronary angioplasty (PTCA) patients. Suitable view schemas for various user roles (cath-lab physician, ward nurse, general practitioner) have been modeled and implemented on the basis of a detailed analysis of the considered clinical environment, carried out by an object-oriented approach.

Algorithms↗