A computational environment for medical diagnosis support systems

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2199, Issue , 2001, Pages 42-47

  Alves, Victor ^a   Neves, José ^a   Maia, Moreira ^b   Nelas, Luís ^b  

^a UNIVERSITY OF MINHO   (Portugal)

^b Centro de Tomografia de Braga   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

COMPETITION; DATA MINING; MEDICAL INFORMATION SYSTEMS; NETWORK SECURITY;

AUTOMATICALLY GENERATED; COMPETITIVE ADVANTAGE; COMPUTATIONAL ENVIRONMENTS; HEALTH CARE PROVIDERS; INTELLIGENT DIAGNOSIS SYSTEM; MACHINE LEARNING TECHNOLOGY; MEDICAL DIAGNOSIS SUPPORT; MEDICAL DIAGNOSTICS;

DIAGNOSIS;

EID: 48049116778     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45497-7_6     Document Type: Conference Paper

References (3)

1. Agrawal, R., Mannila, H., Srikant, R., Toivonem, H., and Verkamo A.I. Fast Discovery of Association Rules., in U.M.Fayad, G. Piatetsky. Shapiro, P.Smith, and R. Uthurusamy, editors. Advances in Knowledge Discovery and Data Mining, pages 307-328, The AAAI/MIT Press, 1995.
2. Neves, J., Alves V., Nelas L., Maia M., and Cruz R. A Multi-Feature Image Classification System that Reduces the Cost-of-Quality Expenditure., in Proceedings of the Second ICSC Symposium on Engineering of Intelligent Systems, Paisley, Scotland, UK, 2000.
3. Alves, J. Neves, M. Maia, L. Nelas.. Computer Tomography based Diagnosis using Extended logic programming and Artificial Neural Networks.. Proceedings of the NAISO Congress on Information Science Innovations ISI2001, Dubai, U.A.E., March 17-21, 2001.