Engstrom, P. F., Arnoletti, J. P., Benson, A. B., Chen, Y.-J., Choti, M. A., Cooper, H. S., … Willett, C. (2009). Colon Cancer. Journal of the National Comprehensive Cancer Network, 7(8), 778-831. doi:10.6004/jnccn.2009.0056
Taniyama, T. K., Hashimoto, K., Kastumata, N., Hirakawa, A., Yonemori, K., Yunokawa, M., … Fujiwara, Y. (2014). Can oncologists predict survival for patients with progressive disease after standard chemotherapies? Current Oncology, 21(2), 84. doi:10.3747/co.21.1743
Kishore, J., Goel, M., & Khanna, P. (2010). Understanding survival analysis: Kaplan-Meier estimate. International Journal of Ayurveda Research, 1(4), 274. doi:10.4103/0974-7788.76794
[+]
Engstrom, P. F., Arnoletti, J. P., Benson, A. B., Chen, Y.-J., Choti, M. A., Cooper, H. S., … Willett, C. (2009). Colon Cancer. Journal of the National Comprehensive Cancer Network, 7(8), 778-831. doi:10.6004/jnccn.2009.0056
Taniyama, T. K., Hashimoto, K., Kastumata, N., Hirakawa, A., Yonemori, K., Yunokawa, M., … Fujiwara, Y. (2014). Can oncologists predict survival for patients with progressive disease after standard chemotherapies? Current Oncology, 21(2), 84. doi:10.3747/co.21.1743
Kishore, J., Goel, M., & Khanna, P. (2010). Understanding survival analysis: Kaplan-Meier estimate. International Journal of Ayurveda Research, 1(4), 274. doi:10.4103/0974-7788.76794
Silva, A., Oliveira, T., Novais, P., Neves, J., & Leão, P. (2016). Developing an Individualized Survival Prediction Model for Colon Cancer. Advances in Intelligent Systems and Computing, 87-95. doi:10.1007/978-3-319-40114-0_10
Hanley, J. A., & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143(1), 29-36. doi:10.1148/radiology.143.1.7063747
Valentini, V., van Stiphout, R. G. P. M., Lammering, G., Gambacorta, M. A., Barba, M. C., Bebenek, M., … Lambin, P. (2011). Nomograms for Predicting Local Recurrence, Distant Metastases, and Overall Survival for Patients With Locally Advanced Rectal Cancer on the Basis of European Randomized Clinical Trials. Journal of Clinical Oncology, 29(23), 3163-3172. doi:10.1200/jco.2010.33.1595
Renfro, L. A., Grothey, A., Xue, Y., Saltz, L. B., André, T., Twelves, C., … Sargent, D. J. (2014). ACCENT-Based Web Calculators to Predict Recurrence and Overall Survival in Stage III Colon Cancer. JNCI: Journal of the National Cancer Institute, 106(12). doi:10.1093/jnci/dju333
Weiser, M. R., Gönen, M., Chou, J. F., Kattan, M. W., & Schrag, D. (2011). Predicting Survival After Curative Colectomy for Cancer: Individualizing Colon Cancer Staging. Journal of Clinical Oncology, 29(36), 4796-4802. doi:10.1200/jco.2011.36.5080
Chang, G. J., Hu, C.-Y., Eng, C., Skibber, J. M., & Rodriguez-Bigas, M. A. (2009). Practical Application of a Calculator for Conditional Survival in Colon Cancer. Journal of Clinical Oncology, 27(35), 5938-5943. doi:10.1200/jco.2009.23.1860
Al-Bahrani, R., Agrawal, A., & Choudhary, A. (2013). Colon cancer survival prediction using ensemble data mining on SEER data. 2013 IEEE International Conference on Big Data. doi:10.1109/bigdata.2013.6691752
Al-Bahrani, R., Agrawal, A., & Choudhary, A. (2017). Survivability prediction of colon cancer patients using neural networks. Health Informatics Journal, 25(3), 878-891. doi:10.1177/1460458217720395
Wang, S. J., Wissel, A. R., Luh, J. Y., Fuller, C. D., Kalpathy-Cramer, J., & Thomas, C. R. (2011). An Interactive Tool for Individualized Estimation of Conditional Survival in Rectal Cancer. Annals of Surgical Oncology, 18(6), 1547-1552. doi:10.1245/s10434-010-1512-3
Kourou, K., Exarchos, T. P., Exarchos, K. P., Karamouzis, M. V., & Fotiadis, D. I. (2015). Machine learning applications in cancer prognosis and prediction. Computational and Structural Biotechnology Journal, 13, 8-17. doi:10.1016/j.csbj.2014.11.005
Jing Han, Haihong E, Guan Le, & Jian Du. (2011). Survey on NoSQL database. 2011 6th International Conference on Pervasive Computing and Applications. doi:10.1109/icpca.2011.6106531
Zafar, R., Yafi, E., Zuhairi, M. F., & Dao, H. (2016). Big Data: The NoSQL and RDBMS review. 2016 International Conference on Information and Communication Technology (ICICTM). doi:10.1109/icictm.2016.7890788
Chawla, N. V. (s. f.). Data Mining for Imbalanced Datasets: An Overview. Data Mining and Knowledge Discovery Handbook, 853-867. doi:10.1007/0-387-25465-x_40
RapidMiner Documentation: Operator Reference Guidehttps://docs.rapidminer.com/latest/studio/operators/
Breiman, L. (1996). Bagging predictors. Machine Learning, 24(2), 123-140. doi:10.1007/bf00058655
Freund, Y., & Schapire, R. E. (1997). A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting. Journal of Computer and System Sciences, 55(1), 119-139. doi:10.1006/jcss.1997.1504
Džeroski, S., & Ženko, B. (2004). Is Combining Classifiers with Stacking Better than Selecting the Best One? Machine Learning, 54(3), 255-273. doi:10.1023/b:mach.0000015881.36452.6e
Kittler, J. (1998). Combining classifiers: A theoretical framework. Pattern Analysis and Applications, 1(1), 18-27. doi:10.1007/bf01238023
Bradley, A. P. (1997). The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition, 30(7), 1145-1159. doi:10.1016/s0031-3203(96)00142-2
Papazoglou, M. P., & van den Heuvel, W.-J. (2007). Service oriented architectures: approaches, technologies and research issues. The VLDB Journal, 16(3), 389-415. doi:10.1007/s00778-007-0044-3
Top 5 Considerations When Evaluating NoSQL Databaseshttps://www.ascent.tech/wp-content/uploads/documents/mongodb/10gen-top-5-nosql-considerations-february-2015.pdf
[-]