Introduction: paradigms for machine learning
Machine learning: paradigms and methods
Connectionist learning procedures
Machine learning: paradigms and methods
Classifier systems and genetic algorithms
Machine learning: paradigms and methods
The nature of statistical learning theory
The nature of statistical learning theory
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Machine Learning
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Data mining a diabetic data warehouse
Artificial Intelligence in Medicine
Journal of Biomedical Informatics - Special issue: Building nursing knowledge through infomatics: from concept representation to data mining
Mining product maps for new product development
Expert Systems with Applications: An International Journal
Intelligent physician segmentation and management based on KDD approach
Expert Systems with Applications: An International Journal
Mining customer knowledge for product line and brand extension in retailing
Expert Systems with Applications: An International Journal
Ontology-based data mining approach implemented for sport marketing
Expert Systems with Applications: An International Journal
Quantitative motor function evaluation: the VAMA project experience
Proceedings of the 2009 conference on Computational Intelligence and Bioengineering: Essays in Memory of Antonina Starita
Backcalculation of pavement layer moduli and Poisson's ratio using data mining
Expert Systems with Applications: An International Journal
Review: Knowledge discovery in medicine: Current issue and future trend
Expert Systems with Applications: An International Journal
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Health care information systems tend to capture data for nursing tasks, and have little basis in nursing knowledge. Opportunity lies in an important issue where the knowledge used by expert nurses (nursing knowledge workers) in caring for patients is undervalued in the health care system. The complexity of nursing's knowledge base remains poorly articulated and inadequately represented in contemporary information systems. There is opportunity for data mining methods to assist with discovering important linkages between clinical data, nursing interventions, and patient outcomes. Following a brief overview of relevant data mining techniques, a preterm risk prediction case study illustrates the opportunities and describes typical data mining issues in the nontrivial task of building knowledge. Building knowledge in nursing, using data mining or any other method, will make progress only if important data that capture expert nurses' contributions are available in clinical information systems configurations.