View Prostate Cancer (public)
- Summary
(A) Tumor versus Normal classification. (B) Prediction of clinical outcome
- License
- unknown (from UCI repository)
- Dependencies
- Tags
- cancer Prediction prostate tumor
- Attribute Types
- Download
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- Original Data Format
- zip
- Name
- Version mldata
- Comment
- Names
- Data (first 10 data points)
ZIP archive prostate/prostate_outcome.data, prostate/prostate_outcome.names, prostate/prostate_TumorVSNormal.names, prostate/prostate_TumorVSNormal_test.data, prostate/prostate_TumorVSNormal_train.data, prostate/, prostate_tumorVSNormal_test.arff, prostate_tumorVSNormal_train.arff, prostate_outcome.arff
- Description
(A) Tumor versus Normal classification: training set (from (1)) contains 52 prostate tumor samples and 50 non-tumor (labelled as "Normal") prostate samples with around 12600 genes. An independent set of testing samples from (2) is also prepared, which is from a different experiment and has a nearly 10-fold difference in overall microarray intensity from the training data. Besides, we have removed extra genes contained in the testing samples. In the above publication, the testing set is indicated to have 27 tumor and 8 normal samples. However, from our extraction, there are 25 tumor and 9 normal samples. (B) Prediction of clinical outcome: in this data set, 21 patients were evaluable with respect to recurrence following surgery with 8 patients having relapsed and 13 patients having remained relapse free ("non-relapse") for at least 4 years.
- URLs
- http://datam.i2r.a-star.edu.sg/datasets/krbd/ProstateCancer/ProstateCancer.html
- Publications
- Data Source
- http://datam.i2r.a-star.edu.sg/datasets/krbd/ProstateCancer/ProstateCancer.html
- Measurement Details
- Usage Scenario
- revision 1
- by kidzik on 2011-09-05 18:27
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Acknowledgements
This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
http://www.pascal-network.org/.