A Knowledge Discovery Methodology for Identifying Vulnerability Factors of Mental Disorder in an Intellectually Disabled Population

Authors:
Xavier Lluis Martorell;Raimon Massanet Vila;Karina Gibert;Miquel Sànchez-Marrè;Juan Carlos Martín;Almudena Martorell
Affiliations:
Facultat d'Informàtica de Barcelona, Barcelona;Facultat d'Informàtica de Barcelona, Barcelona;Knowledge Engineering and Machine Learning Group, UPC, Barcelona and Estadística i Investigació Operativa, Universitat Politècnica de Catalunya, Barcelona;Knowledge Engineering and Machine Learning Group, UPC, Barcelona and Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, Barcelona;Estadística i Investigació Operativa, Universitat Politècnica de Catalunya, Barcelona;Carmen Pardo-Valcarce Foundation, Madrid
Venue:
Proceedings of the 2007 conference on Artificial Intelligence Research and Development
Year:
2007

Citing 3
Cited 0

From data mining to knowledge discovery: an overview

Advances in knowledge discovery and data mining
Short Communication: GESCONDA: An intelligent data analysis system for knowledge discovery and management in environmental databases

Environmental Modelling & Software
Improving similarity assessment with entropy-based local weighting

ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a knowledge discovery methodology for generating new hypothesis to a particular knowledge theory. A combination of AI and Statistical techniques is proposed to increase the corpus of current knowledge of the target domain. In this paper a particular application to analyze comorbid mental disorders with intellectual disability is presented as an example.