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» Mining risk patterns in medical data
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KDD
1994
ACM
96views Data Mining» more  KDD 1994»
13 years 11 months ago
DICE: A Discovery Environment Integrating Inductive Bias
: Most of Knowledge Discovery in Database (KDD) systems are integrating efficient Machine Learning techniques. In fact issues in Machine Learning and KDD are very close allowing fo...
Jean-Daniel Zucker, Vincent Corruble, J. Thomas, G...
KDD
2003
ACM
142views Data Mining» more  KDD 2003»
14 years 7 months ago
Frequent-subsequence-based prediction of outer membrane proteins
A number of medically important disease-causing bacteria (collectively called Gram-negative bacteria) are noted for the extra "outer" membrane that surrounds their cell....
Rong She, Fei Chen 0002, Ke Wang, Martin Ester, Je...
SIGMOD
2010
ACM
249views Database» more  SIGMOD 2010»
13 years 7 months ago
Worry-free database upgrades: automated model-driven evolution of schemas and complex mappings
Schema evolution is an unavoidable consequence of the application development lifecycle. The two primary schemas in an application, the client conceptual object model and the pers...
James F. Terwilliger, Philip A. Bernstein, Adi Unn...
SIGMOD
2007
ACM
195views Database» more  SIGMOD 2007»
14 years 7 months ago
Effective variation management for pseudo periodical streams
Many database applications require the analysis and processing of data streams. In such systems, huge amounts of data arrive rapidly and their values change over time. The variati...
Lv-an Tang, Bin Cui, Hongyan Li, Gaoshan Miao, Don...
KDD
2002
ACM
148views Data Mining» more  KDD 2002»
14 years 7 months ago
Tumor cell identification using features rules
Advances in imaging techniques have led to large repositories of images. There is an increasing demand for automated systems that can analyze complex medical images and extract me...
Bin Fang, Wynne Hsu, Mong-Li Lee