César Montes

Combining expert knowledge and data mining in a medical diagnosis domain

Abstract The medical diagnosis system described here uses underlying knowledge in the isokinetic domain, obtained by combining the expertise of a physician specialised in isokinetic techniques and data mining techniques applied to a set of existing data. An isokinetic machine is basically a physical support on which patients exercise one of their joints, in this case the knee, according to different ranges of movement and at a constant speed. The data on muscle strength supplied by the machine are processed by an expert system that has built-in knowledge elicited from an expert in isokinetics. It cleans and pre-processes the data and conducts an intelligent analysis of the parameters and morphology of the isokinetic curves. Data mining methods based on the discovery of sequential patterns in time series and the fast Fourier transform, which identifies similarities and differences among exercises, were applied to the processed information to characterise injuries and discover reference patterns specific to populations. The results obtained were applied in two environments: one for the blind and another for elite athletes.

Teaching communication skills to hearing-impaired children

The Mehida multimedia system offers hearing-impaired children an easy and appealing way to learn how to communicate with their hearing and deaf peers. Mehida helps them acquire various communication skills simultaneously: sign language, speech, fingerspelling, lip reading, reading, and writing. Didactic activities and games teach the different means of communication. A character shaped like a pear assists and guides the children, explaining each activity and encouraging the children to identify with it throughout the process.

Discovering Similar Patterns for Characterizing Time Series in a Medical Domain

Abstract.In this article, we describe the process of discovering similar patterns in time series and creating reference models for population groups in a medical domain, and particularly in the field of physiotherapy, using data mining techniques on a set of isokinetic data. The discovered knowledge was evaluated against the expertise of a physician specialized in isokinetic techniques, and applied in the I4 (Intelligent Interpretation of Isokinetic Information) project developed in conjunction with the Spanish National Center for Sports Research and Sciences for muscular diagnosis and rehabilitation, injury prevention, training evaluation and planning, etc., of elite athletes and ordinary people.

SONIA: a methodology for natural agent development

Agent-Oriented Software Engineering has emerged as a powerful engineering discipline that can deal with the complexity of todays software systems (primarily in distributed and open environments) better than other more traditional approaches. However, AOSE does not provide a software development process that naturally leads, if the problem so requires, to an agent architecture. Current agent development methodologies have two separate drawbacks. One is that development processes tend to target an agent organization, which is not necessarily always the best structure, as of the requirements definition stage. The other is that the identification and design of agents are complex, and designer experience plays an essential role in their definition. In this paper, we present the SONIA methodology (Set of mOdels for a Natural Identification of Agents) in an attempt to solve these problems. Based on a generic problem-independent analysis and a bottom-up agent identification process, SONIA naturally outputs an agent-based system.

An incremental solution for developing knowledge-based software: its application to an expert system for isokinetics interpretation

Many researchers working in the field of knowledge engineering (KE) are now concerned with identifying a model suitable for developing knowledge-based software and, especially, expert systems (ES). It is important to find a standard model that meets current needs and incorporates techniques successfully implemented in SE (object- or event-orientation, etc.), which are also of keen interest in KE. In this paper, we present an iterative and incremental solution for developing ES, according to which the system domain is derived naturally from the problem domain, thus surmounting the problems now involved in the transition from the conceptual model of the problem to the formal model of the system. As compared with conventional development models, this solution encompasses five main tools, which are: • Use cases with their respective actor interaction diagrams and activity flow diagrams in order to specify the expert system. • The concept dictionary, which allows knowledge engineers to define, bound and select the meaning of each concept used by experts. • The static conceptual model, which provides an overview (concepts and their relations) of the expert system (ES) modelled. • The control and process model, which models the knowledge and metaknowledge used by the expert to attain a goal. • An object-oriented metamodel, which outputs the formal knowledge model, providing an efficient, reusable, extendible and easy-to-implement ES architecture. To demonstrate the robustness of this solution, we describe how it was applied to an ES that interprets the graphs output by an isokinetics machine for a blind person. An isokinetics machine assesses the strength of the muscles of the leg, arm, etc.

An expert system for homeopathic glaucoma treatment (SEHO)

Abstract In this article, an Expert System for Homeopathic Glaucoma Treatment (SEHO) is presented, the task of which is to assist ophthalmologists in selecting the most appropriate therapy for a patient diagnosed as having glaucoma. It is based on techniques proper to homeopathic medicine, a trend that is gaining more and more supporters all over the world, but in which real experts are few and far between. After a brief overview of the state of the art, the authors describe in detail on the development of the system, for which the IDEAL methodology, designed for knowledge-based system development, was used.

Discovering similar patterns for characterising time series in a medical domain

In this article, we describe the process of discovering similar patterns in time series and creating reference models for population groups in a medical domain, and particularly in the field of physiotherapy, using data mining techniques on a set of isokinetic data. The discovered knowledge was evaluated against the expertise of a physician specialising in isokinetic techniques, and applied in the I4 (Intelligent Interpretation of Isokinetic Information) project developed in conjunction with the Spanish National Centre for Sports Research and Sciences and the School of Physiotherapy of the Spanish National Organisation for the Blind for muscular diagnosis and rehabilitation, injury prevention, training evaluation and planning, etc., of elite and blind athletes.

Towards a Natural Agent Paradigm Development Methodology

It is indisputable that software development using agents and, more specifically, the multi-agent systems concept has greater potential for dealing with complex problems than other more traditional approaches. The agent paradigm is acquiring the status of an engineering discipline and gradually leaving the laboratory and moving into industry. However, it has two major omissions: it is missing an agent modeling language and a consolidated development process such as the object paradigm now has. Although we do not provide a definitive answer to this question in this paper, we do try to help to solve the problem as it relates to the agent-oriented development process by considering what features an agent-based development methodology should have, pointing out the omissions of current methodologies and presenting the SONIA methodology that includes the required features.

Functions, rules and models: three complementary techniques for analyzing strength data

Isokinetics systems are now a leading technology for assessing muscle strength and diagnosing muscle injuries. These systems are very expensive, for which reason they should be put to the best possible use. However, the computer interfaces that now come with isokinetics systems only provide a simple graphical display of the strength data, that is, do not interpretate the data. This paper presents the first phase of the I4 (Interface for Intelligent Interpretation of Isokinetie Data) project, which output two computer systems: ISODEPOR and ISOCIH. Both applications provide simple and effective interaction with the LIDO Isokinetics Machine, implementing expertise in the assessment of the data through a knowledge representation mechanism that includes functions, rules and isokinetic models. The main difference between the applications is that while ISODEPOR was built for sports physicians, ISOCIN was built for blind physicians, accounting for their specific impairments.

Knowledge Discovery Using Medical Data Mining

In this paper we describe the process of discovering underlying knowledge in a set of isokinetic tests (continuous time series) using data mining techniques. The methods used are based on the discovery of sequential patterns in time series and the search for similarities and differences among exercises. They were applied to the processed information in order to characterise injuries and discover reference models specific to populations. The discovered knowledge was evaluated against the expertise of a physician specialised in isokinetic techniques and applied in the I4 project (Intelligent Interpretation of Isokinetic Information).