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ICDM
2007
IEEE
118views Data Mining» more  ICDM 2007»
15 years 6 months ago
Predictive Data Mining for Lung Nodule Interpretation
Diagnostic decision-making in pulmonary medical imaging has been improved by computer-aided diagnosis (CAD) systems, serving as second readers to detect suspicious nodules for dia...
William Horsthemke, Ekarin Varutbangkul, Daniela S...
BMCBI
2010
104views more  BMCBI 2010»
14 years 12 months ago
Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies
Background: All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloi...
Maria Pamela C. David, Gisela P. Concepcion, Eduar...
RECOMB
2004
Springer
16 years 4 days ago
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...
INFSOF
2007
139views more  INFSOF 2007»
14 years 11 months ago
Predicting software defects in varying development lifecycles using Bayesian nets
An important decision problem in many software projects is when to stop testing and release software for use. For many software products, time to market is critical and therefore ...
Norman E. Fenton, Martin Neil, William Marsh, Pete...
ML
2000
ACM
185views Machine Learning» more  ML 2000»
14 years 11 months ago
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
Twenty-two decision tree, nine statistical, and two neural network algorithms are compared on thirty-two datasets in terms of classification accuracy, training time, and (in the ca...
Tjen-Sien Lim, Wei-Yin Loh, Yu-Shan Shih