Autonomous decision-making: a data mining approach

The researchers and practitioners of today create models, algorithms, functions, and other constructs defined in abstract spaces. The research of the future will likely be data driven. Symbolic and numeric data that are becoming available in large volumes will define the need for new data analysis t...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2000-12, Vol.4 (4), p.274-284
Hauptverfasser:	Kusiak, A., Kern, J.A., Kernstine, K.H., Tseng, B.T.L.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Algorithms Artificial intelligence Clustering algorithms Computational complexity Computer aided diagnosis Computer simulation Data analysis Data Interpretation, Statistical Data mining Databases, Factual Decision making Decision Making, Computer-Assisted Feature extraction Hospital data processing Humans Learning systems Lung Neoplasms - diagnosis Machine learning algorithms Medical applications Medical diagnostic imaging Neural networks Oncology Set theory
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