{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T03:14:07Z","timestamp":1769829247101,"version":"3.49.0"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,7,19]],"date-time":"2024-07-19T00:00:00Z","timestamp":1721347200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,7,19]],"date-time":"2024-07-19T00:00:00Z","timestamp":1721347200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Inf Syst Front"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s10796-024-10517-7","type":"journal-article","created":{"date-parts":[[2024,7,18]],"date-time":"2024-07-18T23:40:36Z","timestamp":1721346036000},"page":"1209-1225","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Parsimonious Tree Augmented Naive Bayes Model for Exploring Colorectal Cancer Survival Factors and Their Conditional Interrelations"],"prefix":"10.1007","volume":"27","author":[{"given":"Ali","family":"Dag","sequence":"first","affiliation":[]},{"given":"Abdullah","family":"Asilkalkan","sequence":"additional","affiliation":[]},{"given":"Osman T.","family":"Aydas","sequence":"additional","affiliation":[]},{"given":"Musa","family":"Caglar","sequence":"additional","affiliation":[]},{"given":"Serhat","family":"Simsek","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8857-5148","authenticated-orcid":false,"given":"Dursun","family":"Delen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,19]]},"reference":[{"key":"10517_CR1","doi-asserted-by":"publisher","unstructured":"Aarts, E.H., & van Laarhoven, P.J. (1987). Simulated annealing: a pedestrian review of the theory and some applications. Pattern recognition theory and applications, 179\u2013192, https:\/\/doi.org\/10.1007\/978-3-642-83069-3_15","DOI":"10.1007\/978-3-642-83069-3_15"},{"key":"10517_CR2","unstructured":"ACS (2020). American cancer society: Colorectal cancer key statistics. Retrieved from https:\/\/www.cancer.org\/cancer\/colon-rectal-cancer\/about\/key-statistics.html#references"},{"key":"10517_CR3","doi-asserted-by":"crossref","unstructured":"Agresti, A. (2003). Categorical data analysis (Vol. 482). John Wiley & Sons.","DOI":"10.1002\/0471249688"},{"issue":"3","key":"10517_CR4","doi-asserted-by":"publisher","first-page":"878","DOI":"10.1177\/1460458217720395","volume":"25","author":"R Al-Bahrani","year":"2019","unstructured":"Al-Bahrani, R., Agrawal, A., & Choudhary, A. (2019). Survivability prediction of colon cancer patients using neural networks. Health Informatics Journal, 25(3), 878\u2013891. https:\/\/doi.org\/10.1177\/1460458217720395","journal-title":"Health Informatics Journal"},{"key":"10517_CR5","doi-asserted-by":"publisher","unstructured":"Ben-Gal, I. (2008). Bayesian networks. Encyclopedia of statistics in quality and reliability, 1, https:\/\/doi.org\/10.1002\/9780470061572.eqr089","DOI":"10.1002\/9780470061572.eqr089"},{"issue":"12","key":"10517_CR6","doi-asserted-by":"publisher","first-page":"2162","DOI":"10.1111\/poms.12896","volume":"27","author":"M Bjarnadottir","year":"2018","unstructured":"Bjarnadottir, M., Anderson, D., Zia, L., & Rhoads, K. (2018). Predicting colorectal cancer mortality: Models to facilitate patient-physician conversations and inform operational decision making. Production and Operations Management, 27(12), 2162\u20132183. https:\/\/doi.org\/10.1111\/poms.12896","journal-title":"Production and Operations Management"},{"key":"10517_CR7","doi-asserted-by":"publisher","unstructured":"Bottaci, L., Drew, P.J., Hartley, J.E., Hadfield, M.B., Farouk, R., Lee, P.W., . . . Monson, J.R. (1997). Artificial neural networks applied to outcome prediction for colorectal cancer patients in separate institutions. The Lancet, 350 (9076), 469\u2013472, https:\/\/doi.org\/10.1016\/S0140-6736(96)11196-X","DOI":"10.1016\/S0140-6736(96)11196-X"},{"key":"10517_CR8","unstructured":"Bunn, C.C., Du, M., Niu, K., Johnson, T.R., Poston, W.S.C., Foreyt, J.P. (1999). Predicting the risk of obesity using a Bayesian network. Proceedings of the AMIA symposium (p. 1035). Retrieved from https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC2232520\/"},{"key":"10517_CR9","doi-asserted-by":"crossref","unstructured":"Burke, H.B., Goodman, P.H., Rosen, D.B., Henson, D.E., Weinstein, J.N., Harrell Jr, F.E., . . . Bostwick, D.G. (1997). Artificial neural networks improve the accuracy of cancer survival prediction. Cancer , 79 (4), 857\u2013862, 10.1002\/ (SICI)1097\u20130142(19970215)79:4h857::AID-CNCR24i3.0.CO;2-Y","DOI":"10.1002\/(SICI)1097-0142(19970215)79:4<857::AID-CNCR24>3.0.CO;2-Y"},{"issue":"10","key":"10517_CR10","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.1377\/hlthaff.2013.1040","volume":"32","author":"J Bylander","year":"2013","unstructured":"Bylander, J. (2013). Confronting a crisis in cancer care delivery. Health Affairs, 32(10), 1695\u20131697. https:\/\/doi.org\/10.1377\/hlthaff.2013.1040","journal-title":"Health Affairs"},{"key":"10517_CR11","doi-asserted-by":"publisher","unstructured":"Chan, J.A., Meyerhardt, J.A., Niedzwiecki, D., Hollis, D., Saltz, L.B., Mayer, R.J., . . . others (2008). Association of family history with cancer recurrence and survival among patients with stage iii colon cancer. Jama, 299 (21), 2515\u20132523, https:\/\/doi.org\/10.1001\/jama.299.21.2515","DOI":"10.1001\/jama.299.21.2515"},{"key":"10517_CR12","unstructured":"Cheng, J., Bell, D.A., Liu, W. (1997). An algorithm for Bayesian network construction from data. Sixth international workshop on artificial intelligence and statistics (pp. 83\u201390)."},{"issue":"3","key":"10517_CR13","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1109\/TIT.1968.1054142","volume":"14","author":"C Chow","year":"1968","unstructured":"Chow, C., & Liu, C. (1968). Approximating discrete probability distributions with dependence trees. IEEE Transactions on Information Theory, 14(3), 462\u2013467. https:\/\/doi.org\/10.1109\/TIT.1968.1054142","journal-title":"IEEE Transactions on Information Theory"},{"key":"10517_CR14","doi-asserted-by":"publisher","first-page":"117693511882280","DOI":"10.1177\/1176935118822804","volume":"18","author":"C Cockrell","year":"2019","unstructured":"Cockrell, C., & Axelrod, D. E. (2019). Optimization of dose schedules for chemotherapy of early colon cancer determined by high-performance computer simulations. Cancer Informatics, 18, 1176935118822804. https:\/\/doi.org\/10.1177\/1176935118822804","journal-title":"Cancer Informatics"},{"key":"10517_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.dss.2016.02.007","volume":"86","author":"A Dag","year":"2016","unstructured":"Dag, A., Topuz, K., Oztekin, A., Bulur, S., & Megahed, F. M. (2016). A probabilistic data-driven framework for scoring the preoperative recipient-donor heart trans- plant survival. Decision Support Systems, 86, 1\u201312. https:\/\/doi.org\/10.1016\/j.dss.2016.02.007","journal-title":"Decision Support Systems"},{"issue":"12","key":"10517_CR16","doi-asserted-by":"publisher","first-page":"e94","DOI":"10.1097\/PAS.0000000000000749","volume":"40","author":"MA Duggan","year":"2016","unstructured":"Duggan, M. A., Anderson, W. F., Altekruse, S., Penberthy, L., & Sherman, M. E. (2016). The surveillance, epidemiology and end results (seer) program and pathology: Towards strengthening the critical relationship. The American Journal of Surgical Pathology, 40(12), e94. https:\/\/doi.org\/10.1097\/PAS.0000000000000749","journal-title":"The American Journal of Surgical Pathology"},{"issue":"20","key":"10517_CR17","doi-asserted-by":"publisher","first-page":"2398","DOI":"10.1200\/JCO.2015.63.6696","volume":"34","author":"AS Epstein","year":"2016","unstructured":"Epstein, A. S., Prigerson, H. G., O\u2019Reilly, E. M., & Maciejewski, P. K. (2016). Discussions of life expectancy and changes in illness understanding in patients with advanced cancer. Journal of Clinical Oncology, 34(20), 2398. https:\/\/doi.org\/10.1200\/JCO.2015.63.6696","journal-title":"Journal of Clinical Oncology"},{"key":"10517_CR18","doi-asserted-by":"publisher","unstructured":"Feletto, E., Yu, X.Q., Lew, J.-B., St John, D.J.B., Jenkins, M.A., Macrae, F.A., . . . Canfell, K. (2019). Trends in colon and rectal cancer incidence in Australia from 1982 to 2014: analysis of data on over 375,000 cases. Cancer Epidemiology and Prevention Biomarkers, 28 (1), 83\u201390, https:\/\/doi.org\/10.1158\/1055-9965.EPI","DOI":"10.1158\/1055-9965.EPI"},{"key":"10517_CR19","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1023\/A:1007465528199","volume":"29","author":"N Friedman","year":"1997","unstructured":"Friedman, N., Geiger, D., & Goldszmidt, M. (1997). Bayesian network classifiers. Machine learning, 29, 131\u2013163. https:\/\/doi.org\/10.1023\/A:1007465528199","journal-title":"Bayesian network classifiers. Machine learning"},{"key":"10517_CR20","doi-asserted-by":"publisher","unstructured":"Gao, P., Zhou, X., Wang, Z.-n., Song, Y.-x., Tong, L.-l., Xu, Y.-y., . . . Xu, H.-m. (2012). Which is a more accurate predictor in colorectal survival analysis? nine data mining algorithms vs. the TNM staging system. PLoS One, 7 (7), e42015, https:\/\/doi.org\/10.1371\/journal.pone.0042015","DOI":"10.1371\/journal.pone.0042015"},{"issue":"7408","key":"10517_CR21","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1136\/bmj.327.7408.195","volume":"327","author":"P Glare","year":"2003","unstructured":"Glare, P., Virik, K., Jones, M., Hudson, M., Eychmuller, S., Simes, J., & Christakis, N. (2003). A systematic review of physicians\u2019 survival predictions in terminally ill cancer patients. BMJ, 327(7408), 195. https:\/\/doi.org\/10.1136\/bmj.327.7408.195","journal-title":"BMJ"},{"key":"10517_CR22","doi-asserted-by":"publisher","unstructured":"Gramling, R., Fiscella, K., Xing, G., Hoerger, M., Duberstein, P., Plumb, S., . . . others (2016). Determinants of patient-oncologist prognostic discordance in advanced cancer. JAMA oncology , 2 (11), 1421\u20131426, https:\/\/doi.org\/10.1001\/jamaoncol.2016.1861","DOI":"10.1001\/jamaoncol.2016.1861"},{"issue":"4","key":"10517_CR23","doi-asserted-by":"publisher","first-page":"520","DOI":"10.7326\/0003-4819-102-4-520","volume":"102","author":"S Greenfield","year":"1985","unstructured":"Greenfield, S., Kaplan, S., & Ware, J. E., Jr. (1985). Expanding patient involvement in care: Effects on patient outcomes. Annals of Internal Medicine, 102(4), 520\u2013528. https:\/\/doi.org\/10.7326\/0003-4819-102-4-520","journal-title":"Annals of Internal Medicine"},{"key":"10517_CR24","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1007\/b94608","volume":"27","author":"T Hastie","year":"2009","unstructured":"Hastie, T., Tibshirani, R., & Friedman, J. (2009). Springer series in statistics\u2014the elements of statistical learning\u2014data mining. Inference and Prediction, 27, 83\u20135. https:\/\/doi.org\/10.1007\/b94608","journal-title":"Inference and Prediction"},{"key":"10517_CR25","doi-asserted-by":"publisher","unstructured":"Hoerl, A., & Kennard, R. (1988). Ridge regression. Encyclopedia of Statistical Sciences, 8, , https:\/\/doi.org\/10.1002\/0471667196.ess2280.pub2","DOI":"10.1002\/0471667196.ess2280.pub2"},{"key":"10517_CR26","doi-asserted-by":"publisher","unstructured":"Hui, D., Kilgore, K., Nguyen, L., Hall, S., Fajardo, J., Cox-Miller, T.P., . . . others (2011). The accuracy of probabilistic versus temporal clinician prediction of survival for patients with advanced cancer: a preliminary report. The Oncologist, 16 (11), 1642, https:\/\/doi.org\/10.1634\/theoncologist.2011-0173","DOI":"10.1634\/theoncologist.2011-0173"},{"key":"10517_CR27","doi-asserted-by":"publisher","unstructured":"Kane, H.L., Halpern, M.T., Squiers, L.B., Treiman, K.A., McCormack, L.A. (2014). Implementing and evaluating shared decision making in oncology practice. CA: a cancer journal for clinicians, 64, 377\u2013388, https:\/\/doi.org\/10.3322\/caac.21245","DOI":"10.3322\/caac.21245"},{"key":"10517_CR28","doi-asserted-by":"publisher","unstructured":"Karlberg, M., Stenstedt, K., Hallstr\u00a8om, M., Ragnhammar, P., Lenander, C., Edler, D. (2018). Tumor budding versus mismatch repair status in colorectal cancer\u2013an exploratory analysis. Anticancer research, 38 (8), 4713\u20134721, https:\/\/doi.org\/10.21873\/anticanres.12778","DOI":"10.21873\/anticanres.12778"},{"issue":"4598","key":"10517_CR29","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1126\/science.220.4598.671","volume":"220","author":"S Kirkpatrick","year":"1983","unstructured":"Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671\u2013680. https:\/\/doi.org\/10.1126\/science.220.4598.671","journal-title":"Science"},{"issue":"1","key":"10517_CR30","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1097\/COC.0b013e3181cae8dd","volume":"34","author":"P Kornprat","year":"2011","unstructured":"Kornprat, P., Pollheimer, M. J., Lindtner, R. A., Schlemmer, A., Rehak, P., & Langner, C. (2011). Value of tumor size as a prognostic variable in colorectal cancer: A critical reappraisal. American Journal of Clinical Oncology, 34(1), 43\u201349. https:\/\/doi.org\/10.1097\/COC.0b013e3181cae8dd","journal-title":"American Journal of Clinical Oncology"},{"issue":"3","key":"10517_CR31","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1016\/S0277-9536(00)00139-8","volume":"52","author":"\u00d8 Kravdal","year":"2001","unstructured":"Kravdal, \u00d8. (2001). The impact of marital status on cancer survival. Social Science & Medicine, 52(3), 357\u2013368. https:\/\/doi.org\/10.1016\/S0277-9536(00)00139-8","journal-title":"Social Science & Medicine"},{"key":"10517_CR32","doi-asserted-by":"publisher","unstructured":"Kuhn, M., Johnson, K., et al. (2013). Applied predictive modeling (Vol. 26). Springer. Retrieved from https:\/\/link.springer.com\/book\/https:\/\/doi.org\/10.1007\/978-1-4614-6849-3","DOI":"10.1007\/978-1-4614-6849-3"},{"issue":"6","key":"10517_CR33","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1093\/bjaceaccp\/mkn041","volume":"8","author":"AG Lalkhen","year":"2008","unstructured":"Lalkhen, A. G., & McCluskey, A. (2008). Clinical tests: Sensitivity and specificity. Continuing Education in Anesthesia Critical Care & Pain, 8(6), 221\u2013223. https:\/\/doi.org\/10.1093\/bjaceaccp\/mkn041","journal-title":"Continuing Education in Anesthesia Critical Care & Pain"},{"key":"10517_CR34","unstructured":"Lee, C.-H., Cheng, S.-C., TUNG, H.-Y., Chang, S.-C., Ching, C.-Y., Wu, S.F. (2018). The risk factors affecting survival in colorectal cancer in Taiwan. Iranian journal of public health, 47 (4), 519, Retrieved from https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC5996318\/"},{"issue":"3","key":"10517_CR35","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/S0933-3657(00)00048-8","volume":"19","author":"PJ Lucas","year":"2000","unstructured":"Lucas, P. J., de Bruijn, N. C., Schurink, K., & Hoepelman, A. (2000). A probabilistic and decision-theoretic approach to the management of infectious disease at the ICU. Artificial Intelligence in Medicine, 19(3), 251\u2013279. https:\/\/doi.org\/10.1016\/S0933-3657(00)00048-8","journal-title":"Artificial Intelligence in Medicine"},{"key":"10517_CR36","doi-asserted-by":"publisher","unstructured":"Meester, R.G., Peterse, E.F., Knudsen, A.B., de Weerdt, A.C., Chen, J.C., Lietz, A.P., . . . others (2018). Optimizing colorectal cancer screening by race and sex: microsimulation analysis ii to inform the american cancer society colorectal cancer screening guideline. Cancer , 124 (14), 2974\u20132985, https:\/\/doi.org\/10.1002\/cncr.31542","DOI":"10.1002\/cncr.31542"},{"issue":"3","key":"10517_CR37","doi-asserted-by":"publisher","first-page":"842","DOI":"10.1016\/j.ejor.2004.09.010","volume":"171","author":"R Meiri","year":"2006","unstructured":"Meiri, R., & Zahavi, J. (2006). Using simulated annealing to optimize the feature selection problem in marketing applications. European Journal of Operational Research, 171(3), 842\u2013858. https:\/\/doi.org\/10.1016\/j.ejor.2004.09.010","journal-title":"European Journal of Operational Research"},{"key":"10517_CR38","doi-asserted-by":"publisher","unstructured":"Oberije, C., Nalbantov, G., Dekker, A., Boersma, L., Borger, J., Reymen, B., . . . others (2014). A prospective study comparing the predictions of doctors versus models for treatment outcome of lung cancer patients: a step toward individualized care and shared decision making. Radiotherapy and Oncology, 112 (1), 37\u201343, https:\/\/doi.org\/10.1016\/j.radonc.2014.04.012","DOI":"10.1016\/j.radonc.2014.04.012"},{"key":"10517_CR39","doi-asserted-by":"publisher","unstructured":"Oliveira, T., Barbosa, E., Martins, S., Goulart, A., Neves, J., & Novais, P. (2013). A prognosis system for colorectal cancer. In Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems (pp. 481\u2013484). IEEE. https:\/\/doi.org\/10.1109\/cbms.2013.6627846","DOI":"10.1109\/cbms.2013.6627846"},{"key":"10517_CR40","doi-asserted-by":"publisher","unstructured":"Peterse, E.F., Meester, R.G., Siegel, R.L., Chen, J.C., Dwyer, A., Ahnen, D.J., . . . Lansdorp-Vogelaar, I. (2018). The impact of the rising colorectal cancer incidence in young adults on the optimal age to start screening: microsimulation analysis to inform the American cancer society colorectal cancer screening guideline. Cancer, 124 (14), 2964\u20132973, https:\/\/doi.org\/10.1002\/cncr.31543","DOI":"10.1002\/cncr.31543"},{"key":"10517_CR41","doi-asserted-by":"publisher","unstructured":"Qiu, S., Nikolaou, S., Fiorentino, F., Rasheed, S., Darzi, A., Cunningham, D., . . . Kontovounisios, C. (2019). Exploratory analysis of plasma neurotensin as a novel biomarker for early detection of colorectal polyp and cancer. Hormones and Cancer, 10 (2), 128\u2013135, https:\/\/doi.org\/10.1007\/s12672-019-00364-3","DOI":"10.1007\/s12672-019-00364-3"},{"key":"10517_CR42","unstructured":"R Core Team (2020). R: A language and environment for statistical computing [Computer software manual]. Vienna, Austria. Retrieved from http:\/\/www.R- project.org\/"},{"key":"10517_CR43","unstructured":"Sailer, F., Pobiruchin, M., Bochum, S., Martens, U.M., Schramm, W. (2015). Prediction of 5-year survival with data mining algorithms. Icimth (pp. 75\u201378)."},{"issue":"12","key":"10517_CR44","doi-asserted-by":"publisher","first-page":"1716","DOI":"10.1046\/j.1365-2168.1998.00958.x","volume":"85","author":"M Sailer","year":"1998","unstructured":"Sailer, M., Bussen, D., Fuchs, K., & Thiede, A. (1998). Quality of life in patients with benign anorectal disorders. British Journal of Surgery, 85(12), 1716\u20131719. https:\/\/doi.org\/10.1046\/j.1365-2168.1998.00958.x","journal-title":"British Journal of Surgery"},{"issue":"7414","key":"10517_CR45","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1136\/bmj.327.7414.542","volume":"327","author":"RE Say","year":"2003","unstructured":"Say, R. E., & Thomson, R. (2003). The importance of patient preferences in treatment decisions\u2014challenges for doctors. BMJ, 327(7414), 542\u2013545. https:\/\/doi.org\/10.1136\/bmj.327.7414.542","journal-title":"BMJ"},{"key":"10517_CR46","doi-asserted-by":"publisher","unstructured":"Siegel, R., DeSantis, C., Jemal, A. (2014). Colorectal cancer statistics, 2014. CA: a cancer journal for clinicians, 64 (2), 104\u2013117, https:\/\/doi.org\/10.3322\/caac.21220","DOI":"10.3322\/caac.21220"},{"key":"10517_CR47","doi-asserted-by":"crossref","unstructured":"Stewart, B., & Kleihues, P. (2003). World cancer report. International Agency for Research on Cancer.","DOI":"10.1016\/S0140-6736(03)12634-7"},{"key":"10517_CR48","unstructured":"Stiphout, R., Postma, E., Valentini, V., Lambin, P. (2010). The contribution of machine learning to predicting cancer outcome. Artificial Intelligence, 350, 400, Retrieved from http:\/\/bnaic2010.uni.lu\/Papers\/Category%20C\/Postma.pdf"},{"key":"10517_CR49","doi-asserted-by":"publisher","unstructured":"Stojadinovic, A., Bilchik, A., Smith, D., Eberhardt, J.S., Ward, E.B., Nissan, A., . . . others (2013). Clinical decision support and individualized prediction of survival in colon cancer: Bayesian belief network model. Annals of Surgical Oncology, 20 (1), 161\u2013174, https:\/\/doi.org\/10.1245\/s10434-012-2555-4","DOI":"10.1245\/s10434-012-2555-4"},{"issue":"1","key":"10517_CR50","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","volume":"58","author":"R Tibshirani","year":"1996","unstructured":"Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society: Series B (methodological), 58(1), 267\u2013288. https:\/\/doi.org\/10.1111\/j.2517-6161.1996.tb02080.x","journal-title":"Journal of the Royal Statistical Society: Series B (methodological)"},{"issue":"2","key":"10517_CR51","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/S0933-3657(02)00012-X","volume":"25","author":"LC Van der Gaag","year":"2002","unstructured":"Van der Gaag, L. C., Renooij, S., Witteman, C. L., Aleman, B. M., & Taal, B. G. (2002). Probabilities for a probabilistic network: A case study in esophageal cancer. Artificial Intelligence in Medicine, 25(2), 123\u2013148. https:\/\/doi.org\/10.1016\/S0933-3657(02)00012-X","journal-title":"Artificial Intelligence in Medicine"},{"issue":"1\u20132","key":"10517_CR52","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/S0004-3702(98)00010-1","volume":"101","author":"O Vans","year":"1998","unstructured":"Vans, O. (1998). A belief network approach to optimization and parameter estimation: Application to resource and environmental management. Artificial Intelligence, 101(1\u20132), 135\u2013163. https:\/\/doi.org\/10.1016\/S0004-3702(98)00010-1","journal-title":"Artificial Intelligence"},{"key":"10517_CR53","doi-asserted-by":"publisher","unstructured":"Walker, J.G., Bickerstaffe, A., Hewabandu, N., Maddumarachchi, S., Dowty, J.G., Jenkins, M., . . . Emery, J.D. (2017). The crisp colorectal cancer risk prediction tool: an exploratory study using simulated consultations in Australian primary care. BMC Medical Informatics and Decision Making , 17 (1), 1\u201311, https:\/\/doi.org\/10.1186\/s12911-017-0407-7","DOI":"10.1186\/s12911-017-0407-7"},{"issue":"5","key":"10517_CR54","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1016\/j.canep.2011.02.004","volume":"35","author":"L Wang","year":"2011","unstructured":"Wang, L., Wilson, S. E., Stewart, D. B., & Hollenbeak, C. S. (2011). Marital status and colon cancer outcomes in us surveillance, epidemiology and end results registries: Does marriage affect cancer survival by gender and stage? Cancer Epidemiology, 35(5), 417\u2013422. https:\/\/doi.org\/10.1016\/j.canep.2011.02.004","journal-title":"Cancer Epidemiology"},{"issue":"35","key":"10517_CR55","doi-asserted-by":"publisher","first-page":"e1402","DOI":"10.1097\/MD.0000000000001402","volume":"94","author":"R Wang","year":"2015","unstructured":"Wang, R., Wang, M.-J., & Ping, J. (2015). Clinicopathological features and survival outcomes of colorectal cancer in young versus elderly: A population-based cohort study of seer 9 registries data (1988\u20132011). Medicine, 94(35), e1402. https:\/\/doi.org\/10.1097\/MD.0000000000001402","journal-title":"Medicine"},{"issue":"17","key":"10517_CR56","doi-asserted-by":"publisher","first-page":"1616","DOI":"10.1056\/NEJMoa1204410","volume":"367","author":"JC Weeks","year":"2012","unstructured":"Weeks, J. C., Catalano, P. J., Cronin, A., Finkelman, M. D., Mack, J. W., Keating, N. L., & Schrag, D. (2012). Patients\u2019 expectations about effects of chemotherapy for advanced cancer. New England Journal of Medicine, 367(17), 1616\u20131625. https:\/\/doi.org\/10.1056\/NEJMoa1204410","journal-title":"New England Journal of Medicine"},{"key":"10517_CR57","doi-asserted-by":"publisher","unstructured":"Wheeler, S.B., Leeman, J., Lich, K.H., Tangka, F.K., Davis, M.M., Richardson, L.C. (2018). Data-powered participatory decision making: leveraging systems thinking and simulation to guide selection and implementation of evidence-based colorectal cancer screening interventions. Cancer journal (Sudbury, Mass.), 24 (3), 132, https:\/\/doi.org\/10.1097\/PPO.0000000000000317","DOI":"10.1097\/PPO.0000000000000317"},{"key":"10517_CR58","doi-asserted-by":"crossref","unstructured":"Whelan, T.J., Mohide, E.A., Willan, A.R., Arnold, A., Tew, M., Sellick, S., . . . Levine, M.N. (1997). The supportive care needs of newly diagnosed cancer patients attending a regional cancer center. Cancer: Interdisciplinary International Journal of the American Cancer Society, 80 (8), 1518\u20131524, 10.1002\/ (SICI)1097\u20130142(19971015)80:8h1518::AID-CNCR21i3.0.CO;2\u20137","DOI":"10.1002\/(SICI)1097-0142(19971015)80:8<1518::AID-CNCR21>3.0.CO;2-7"},{"issue":"8","key":"10517_CR59","doi-asserted-by":"publisher","first-page":"e0161407","DOI":"10.1371\/journal.pone.0161407","volume":"11","author":"N White","year":"2016","unstructured":"White, N., Reid, F., Harris, A., Harries, P., & Stone, P. (2016). A systematic review of predictions of survival in palliative care: How accurate are clinicians and who are the experts? PLoS ONE, 11(8), e0161407. https:\/\/doi.org\/10.1371\/journal.pone.0161407","journal-title":"PLoS ONE"},{"key":"10517_CR60","unstructured":"Wild, C., Stewart, B., Wild, C. (2014). World cancer report 2014: World health organization Geneva. Switzerland. Retrieved from https:\/\/www.who.int\/cancer\/publications\/WRC 2014\/en\/"},{"key":"10517_CR61","doi-asserted-by":"publisher","unstructured":"Willowson, K.P., Hayes, A.R., Chan, D.L., Tapner, M., Bernard, E.J., Maher, R., . . . Bailey, D.L. (2017). Clinical and imaging-based prognostic factors in radioembolization of liver metastases from colorectal cancer: a retrospective exploratory analysis. EJNMMI Research, 7 (1), 1\u201313, https:\/\/doi.org\/10.1186\/s13550-017-0292-1","DOI":"10.1186\/s13550-017-0292-1"},{"key":"10517_CR62","doi-asserted-by":"publisher","first-page":"2125","DOI":"10.1016\/B978-0-444-64241-7.50349-9","volume":"44","author":"D Young","year":"2018","unstructured":"Young, D., & Cremaschi, S. (2018). A simulation-based optimization approach to develop personalized colorectal cancer screening strategies. Computer Aided Chemical Engineering, 44, 2125\u20132130. https:\/\/doi.org\/10.1016\/B978-0-444-64241-7.50349-9","journal-title":"Computer Aided Chemical Engineering"},{"key":"10517_CR63","unstructured":"Zou, H., & Hastie, T. (2003). Regression shrinkage and selection via the elastic net, with applications to microarrays. JR Stat Soc Ser B, 67, 301\u201320, 221d61b5719c3c66109d476f3b35b1f557a60769"},{"issue":"2","key":"10517_CR64","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","volume":"67","author":"H Zou","year":"2005","unstructured":"Zou, H., & Hastie, T. (2005). Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society: Series B (statistical Methodology), 67(2), 301\u2013320. https:\/\/doi.org\/10.1111\/j.1467-9868.2005.00503.x","journal-title":"Journal of the Royal Statistical Society: Series B (statistical Methodology)"}],"container-title":["Information Systems Frontiers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-024-10517-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10796-024-10517-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-024-10517-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T09:56:17Z","timestamp":1753091777000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10796-024-10517-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,19]]},"references-count":64,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["10517"],"URL":"https:\/\/doi.org\/10.1007\/s10796-024-10517-7","relation":{},"ISSN":["1387-3326","1572-9419"],"issn-type":[{"value":"1387-3326","type":"print"},{"value":"1572-9419","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,19]]},"assertion":[{"value":"26 June 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 July 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"None to declare.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"We, the authors, give our consent for the publisher to publish this article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"None to declare.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}