Ecai 2008 ghallab m spyropoulos c d fakotakis n. Formalizing Dynamics of Mood and Depression — Vrije Universiteit Amsterdam 2019-03-20

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ECAI 2008 (Edited by: M. Ghallab, C.D. Spyropoulos, N. Fakotakis and N. Avouris)

ecai 2008 ghallab m spyropoulos c d fakotakis n

Since our automatically generated textual summaries can be improved by including additional content and expert knowledge, they promise to enhance information exchange between the medical and nursing staff, particularly when integrated with the currently available graphical presentations. In this paper we discuss the main components of our approach with a critical analysis of their strengths and limitations and present options for improvement to address these limitations. The measures Cohen Kappa and Powers Informedness are discussed as unbiased alternative to Recall and related to the psychologically significant measure DeltaP. Unless the data are further processed, it is difficult for medical and nursing staff to assimilate what is important. The algorithm operates on a number of features built by aggregation of different variations of the first and second order pixel gradients related to the aggregated templates of pedestrian and non-pedestrian classes.

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Agent

ecai 2008 ghallab m spyropoulos c d fakotakis n

The main feature of this technology is that it brings together a diverse set of techniques such as medical signal analysis, knowledge based reasoning, medical ontology and natural language generation. The system has been fine-tuned against its parameters and feature subsets and tested using almost 10000 real images provided by DaimlerChrysler. It has been demonstrated that data summarization in natural language has the potential to improve clinical decision making; we have implemented and evaluated a prototype system which generates such textual summaries automatically. The rest of the distribution remains about stable, with marginal fluctuations given that areas are overlapping and their frontiers are not sharp. Such system would have to make safety critical decisions based on poor quality images shot in real-time from the unstable moving vehicles.

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Evaluation Evaluation: a Monte Carlo study

ecai 2008 ghallab m spyropoulos c d fakotakis n

The main feature of this technology is that it brings together a diverse set of techniques such as medical signal analysis, knowledge based reasoning, medical ontology and natural language generation. This paper therefore presents computational models for these interventions for different types of therapy. Unless the data are further processed, it is difficult for medical and nursing staff to assimilate what is important. History of artificial intelligence — Wikipedia Precursors. In this paper we discuss the main components of our approach with a critical analysis of their strengths and limitations and present options for improvement to address these limitations.

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ECAI 2008 (Edited by: M. Ghallab, C.D. Spyropoulos, N. Fakotakis and N. Avouris)

ecai 2008 ghallab m spyropoulos c d fakotakis n

For each class the algorithm fits a fixed number of clusters and using Gaussian kernels optimises the parameters of the Gaussian Mixture model such that the probabilities of belonging to the intra-class clusters is maximised. The program committee decided to accept 121 full papers, an acceptance rate of 23%, and 97 posters. . Cite this paper as: Both F. This 18th edition received more submissions than the previous ones.

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Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units — The University of Aberdeen

ecai 2008 ghallab m spyropoulos c d fakotakis n

Lecture Notes in Computer Science, vol 6334. The rest of the distribution remains about stable, with marginal fluctuations given that areas are overlapping and their frontiers are not sharp. Our evaluation of the computer generated summaries showed that the decisions made by medical and nursing staff after reading the summaries were as good as those made after viewing the currently available graphical presentations with the same information content. Since our automatically generated textual summaries can be improved by including additional content and expert knowledge, they promise to enhance information exchange between the medical and nursing staff, particularly when integrated with the currently available graphical presentations. Since our automatically generated textual summaries can be improved by including additional content and expert knowledge, they promise to enhance information exchange between the medical and nursing staff, particularly when integrated with the currently available graphical presentations. A computational model for human mood regulation and depression has been developed in previous work, but in order for the agent to give optimal support during an intervention, it should also have knowledge on the precise functioning of the intervention in relation with the mood regulation and depression. Given a new image the system instantly generates relative features and uses mixture model to build posterior probability densities for all clusters and after aggregation and renormalisation, posterior class probabilities.

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Evaluation Evaluation: a Monte Carlo study

ecai 2008 ghallab m spyropoulos c d fakotakis n

In this paper we will analyze both biased and unbiased measures theoretically, characterizing the precise relationship between all these measures as well as evaluating the evaluation measures themselves empirically using a Monte Carlo simulation. Such an agent should then have a good idea of the current state of the person. Our evaluation of the computer generated summaries showed that the decisions made by medical and nursing staff after reading the summaries were as good as those made after viewing the currently available graphical presentations with the same information content. Automated pedestrian detection is a forward looking challenge for future driver support systems in automotive industry. In the drive to improve patient safety, patients in modem intensive care units are closely monitored with the generation of very large volumes of data.

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Mixture of Gaussians Model for Robust Pedestrian Images Detection.

ecai 2008 ghallab m spyropoulos c d fakotakis n

The intervention models have been evaluated for a variety of patient types by simulation experiments and formal verification. Several submitted full papers have been accepted as posters. This 18th edition received more submissions than the previous ones. It has been demonstrated that data summarization in natural language has the potential to improve clinical decision making; we have implemented and evaluated a prototype system which generates such textual summaries automatically. All posters, presented in these proceedings as short papers, will have formal presentation slots in the technical sessions of the main program of the conference, as well as poster presentations within a specific session. Our evaluation of the computer generated summaries showed that the decisions made by medical and nursing staff after reading the summaries were as good as those made after viewing the currently available graphical presentations with the same information content. Our evaluation of the computer generated summaries showed that the decisions made by medical and nursing staff after reading the summaries were as good as those made after viewing the currently available graphical presentations with the same information content.

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Agents Preferences in Decentralized Task Allocation — Vrije Universiteit Amsterdam

ecai 2008 ghallab m spyropoulos c d fakotakis n

Simulation results are presented showing that the mood regulation and depression indeed follow the expected patterns when applying these therapies. Several submitted full papers have been accepted as posters. In this paper we discuss the main components of our approach with a critical analysis of their strengths and limitations and present options for improvement to address these limitations. Artificial Intelligence, International Competition, and In early September 2017, Russian President Vladimir Putin brought artificial intelligence from the labs of Silicon Valley, academia, and the basement of the Pentagon to the forefront of international politics. In this paper we discuss the main components of our approach with a critical analysis of their strengths and limitations and present options for improvement to address these limitations.

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ECAI 2008 Proceedings

ecai 2008 ghallab m spyropoulos c d fakotakis n

Artificial Intelligence Internet Encyclopedia of Philosophy Artificial Intelligence. It has been demonstrated that data summarization in natural language has the potential to improve clinical decision making; we have implemented and evaluated a prototype system which generates such textual summaries automatically. In order to make interventions for a depressed patient during a therapy more personalized and effective, a supporting personal software agent can be useful. All posters, presented in these proceedings as short papers, will have formal presentation slots in the technical sessions of the main program of the conference, as well as poster presentations within a specific session. Spyropoulos; Nikos Fakotakis; Nikos Avouris.

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Computational Modeling and Analysis of Therapeutical Interventions for Depression

ecai 2008 ghallab m spyropoulos c d fakotakis n

It has been demonstrated that data summarization in natural language has the potential to improve clinical decision making; we have implemented and evaluated a prototype system which generates such textual summaries automatically. The main feature of this technology is that it brings together a diverse set of techniques such as medical signal analysis, knowledge based reasoning, medical ontology and natural language generation. The main feature of this technology is that it brings together a diverse set of techniques such as medical signal analysis, knowledge based reasoning, medical ontology and natural language generation. Without knowledge of the Bias and Prevalence of the contingency being tested, or equivalently the expectation due to chance, the simple conditional probabilities Recall, Precision and Accuracy are not meaningful as evaluation measures, either individually or in combinations such as F-factor. Since our automatically generated textual summaries can be improved by including additional content and expert knowledge, they promise to enhance information exchange between the medical and nursing staff, particularly when integrated with the currently available graphical presentations. Evaluation Evaluation: a Monte Carlo study. Unless the data are further processed, it is difficult for medical and nursing staff to assimilate what is important.

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