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José Machado

Researcher at University of Minho

Publications -  603
Citations -  4500

José Machado is an academic researcher from University of Minho. The author has contributed to research in topics: Intensive care & Decision support system. The author has an hindex of 26, co-authored 553 publications receiving 3768 citations. Previous affiliations of José Machado include Bosch.

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Book ChapterDOI

Ambient Assisted Living

TL;DR: It is the goal to present the VirtualECare framework, an intelligent multi-agent system able to monitor, interact and serve its customers, which are in need of care services, based in open standards, expecting not only to fulfil the objectives referred to, but also to overcome the problems induced by the use of new technologies and formalisms.
Proceedings ArticleDOI

The halt condition in genetic programming

TL;DR: In this paper, the authors address the role of divergence and convergence in creative processes and argue about the need to consider them in Computational Creativity research in the Genetic or Evolutionary Programming paradigm, being one's goal the problem of the Halt Condition in Genetic Programming.
Journal ArticleDOI

Quality of service in healthcare units

TL;DR: In this article, a web spider of intelligent information processing system is proposed to support the medical applications in terms of an agency for integration, diffusion and archiving of medical information and the electronic medical record.
Journal ArticleDOI

The Next Generation of Interoperability Agents in Healthcare

TL;DR: The importance of monitoring and controlling intelligent agents as a tool to anticipate problems in health information systems is shown and the functionality and the overall usability of AIDA was increased.
Proceedings ArticleDOI

Artificial neural networks in diabetes control

TL;DR: This work will focus on the development of a diagnosis support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centred on Artificial Neural Networks to evaluate the Diabetes states and the Degree ofConfidence that one has on such a happening.