An algorithm for learning rule sets from survival data
UPDATE: LR-rules is now the part of RuleKit - our comprehensive suite for rule-based learning. We suggest using RuleKit for analyses as we constatly improve its functionality and keep it up to date.
Wrobel, L, Gudys, A, Sikora, M (2017) Learning rule sets from survival data, BMC Bioinformatics, 2017 May 30;18(1):285. DOI: 10.1186/s12859-017-1693-x.
- actg320 (HIV-infected patients): ftp://ftp.wiley.com/public/sci_tech_med/survival
- BMT-Ch (bone marrow transplant): https://github.com/adaa-polsl/GuideR/blob/master/datasets/bmt/bone-marrow.arff
- cancer (advanced lung cancer patients): survival R package
- follic (follicular cell lymphoma patients): randomForestSRC R package
- GBSG2 (node-positive breast cancer patients): TH.data R package
- hd (Hodgkin's disease patients): randomForestSRC R package
- LAC (lung adenocarcinoma): pensim R package
- lung (early detection of lung cancer): https://www.stats.ox.ac.uk/pub/datasets/csb
- Melanoma (malignant melanoma patients after radical operation): riskRegression R package
- mgus (patients with monoclonal gammopathy of undetermined significance): survival R package
- pbc (primary biliary cirrhosis of the liver): survival R package
- PTC (papillary thyroid carcinoma): https://github.com/adaa-polsl/LR-Rules/blob/master/data/thyroid.arff
- std (occurrence of sexually transmitted diseases): KMsurv R package
- uis (drug abuse reduction): quantreg R package
- wcgs (occurrence of coronary heart disease): epitools R package
- whas1 (myocardial infarction patients, 1st book edition): ftp://ftp.wiley.com/public/sci_tech_med/survival
- whas500 (myocardial infarction patients, 2nd book edition): ftp://ftp.wiley.com/public/sci_tech_med/survival
- zinc (esophageal cancer): NestedCohort R package