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Biomedical subjects

L Chittaro

Publications and source records attributed to L Chittaro.

4 recordsLinked to original sources
PubMed2001

Information visualization and its application to medicine.

This paper provides an introduction to the field of information visualization (IV) and a discussion of its application to medical systems. More specifically, it aims at: (i) defining what IV is and what are its goals (ii) highlighting the similarities and differences between IV and traditional medical imaging (iii) illustrating the potential of IV for medical applications by examining several examples of implemented systems and (iv) giving some general indications about the purposes and the effective exploitation of an IV component into a medical system.

Artificial Intelligence↗
PubMed1999

Abstraction on clinical data sequences: an object-oriented data model and a query language based on the event calculus.

In this work, we deal with temporal abstraction of clinical data. Abstractions are, for example, blood pressure state (e.g. normal, high, low) and trend (e.g. increasing, decreasing and stationary) over time intervals. The goal of our work is to provide clinicians with automatic tools to extract high-level, concise, important features of available collections of time-stamped clinical data. This capability is especially important when the available collections constantly increase in size, as in long-term clinical follow-up, leading to information overload. The approach we propose exploits the integration of the deductive and object-oriented approaches in clinical databases. The main result of this work is an object-oriented data model based on the event calculus to support temporal abstraction. The proposed approach has been validated building the CARDIOTABS system for the abstraction of clinical data collected during echocardiographic tests.

Databases, Factual↗
PubMed1997

Using a general theory of time and change in patient monitoring: experiment and evaluation.

In this paper, we propose to use one of the well-known general theories of time and change, namely the Event Calculus (Kowalski and Sergot, New Generation Computing 4, 67-95, 1986), to represent temporal aspects in intelligent medical monitoring systems. In particular, we explore the application of CEC (Chittaro and Montanari, Computational Intelligence 12, 359-382, 1996) (an efficient implementation of the Event Calculus) to the management of mechanical ventilation. First, we present the prototype we have built, which has been extensively tested on patient's data from real clinical cases. Then, we provide a thorough evaluation of the obtained results, pointing out both strengths and weaknesses of the approach, and identifying a number of extensions which can be extremely useful to scale up the medical application of the approach.

Artificial Intelligence↗