{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T07:31:52Z","timestamp":1725521512954},"publisher-location":"Berlin, Heidelberg","reference-count":15,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540897217"},{"type":"electronic","value":"9783540897224"}],"license":[{"start":{"date-parts":[[2008,1,1]],"date-time":"2008-01-01T00:00:00Z","timestamp":1199145600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008]]},"DOI":"10.1007\/978-3-540-89722-4_15","type":"book-chapter","created":{"date-parts":[[2008,11,26]],"date-time":"2008-11-26T08:57:14Z","timestamp":1227689834000},"page":"191-204","source":"Crossref","is-referenced-by-count":3,"title":["Use of Reinforcement Learning in Two Real Applications"],"prefix":"10.1007","author":[{"given":"Jos\u00e9 D.","family":"Mart\u00edn-Guerrero","sequence":"first","affiliation":[]},{"given":"Emilio","family":"Soria-Olivas","sequence":"additional","affiliation":[]},{"given":"Marcelino","family":"Mart\u00ednez-Sober","sequence":"additional","affiliation":[]},{"given":"Antonio J.","family":"Serrrano-L\u00f3pez","sequence":"additional","affiliation":[]},{"given":"Rafael","family":"Magdalena-Benedito","sequence":"additional","affiliation":[]},{"given":"Juan","family":"G\u00f3mez-Sanchis","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"15_CR1","unstructured":"Lynne Peterson, L.: FDA Oncologic Drugs Advisory Committee (ODAC) meeting on the safety of erythropoietin in oncology. Trends in Medicine, pp. 1\u20134 (May 2004)"},{"key":"15_CR2","unstructured":"National Kidney\u00a0Foundation, K.D.O.Q.I.: Guidelines for anemia of chronic kidney disease. NKF K\/DOQI Guidelines (2000), \n                  \n                    http:\/\/www.kidney.org"},{"issue":"7","key":"15_CR3","doi-asserted-by":"publisher","first-page":"1079","DOI":"10.1200\/JCO.2005.02.7276","volume":"24","author":"D. Steensma","year":"2006","unstructured":"Steensma, D., Molina, R., Sloan, J., Nikcevich, D., Schaefer, P., Rowland, K.J., Dentchev, T., Novotny, P., Tschetter, L., Alberts, S., Hogan, T., Law, A., Loprinzi, C.L.: Phase III study of two different dosing schedules of erythropoietin in anemic patients with cancer. Journal of Clinical Oncology\u00a024(7), 1079\u20131089 (2006)","journal-title":"Journal of Clinical Oncology"},{"key":"15_CR4","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1006\/cbmr.1993.1019","volume":"26","author":"R. Bellazzi","year":"1992","unstructured":"Bellazzi, R.: Drug delivery optimization through bayesian networks: an application to erythropoietin therapy in uremic anemia. Computers and Biomedical Research\u00a026, 274\u2013293 (1992)","journal-title":"Computers and Biomedical Research"},{"key":"15_CR5","first-page":"154","volume":"79","author":"R. Bellazzi","year":"1994","unstructured":"Bellazzi, R., Siviero, C., Bellazzi, R.: Mathematical modeling of erythropoietin therapy in uremic anemia. Does it improve cost-effectiveness? Haematologica\u00a079, 154\u2013164 (1994)","journal-title":"Does it improve cost-effectiveness? Haematologica"},{"key":"15_CR6","first-page":"387","volume":"12","author":"A.A. Jacobs","year":"2001","unstructured":"Jacobs, A.A., Lada, P., Zurada, J.M., Brier, M.E., Aronoff, G.: Predictors of hematocrit in hemodialysis patients as determined by artificial neural networks. Journal of American Nephrology\u00a012, 387A (2001)","journal-title":"Journal of American Nephrology"},{"issue":"4","key":"15_CR7","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/S0010-4825(02)00065-3","volume":"33","author":"J.D. Mart\u00edn","year":"2003","unstructured":"Mart\u00edn, J.D., Soria, E., Camps, G., Serrano, A., P\u00e9rez, J., Jim\u00e9nez, N.: Use of neural networks for dosage individualisation of erythropoietin in patients with secondary anemia to chronic renal failure. Computers in Biology and Medicine\u00a033(4), 361\u2013373 (2003)","journal-title":"Computers in Biology and Medicine"},{"key":"15_CR8","volume-title":"Reinforcement Learning: An Introducion","author":"R. Sutton","year":"1998","unstructured":"Sutton, R., Barto, A.: Reinforcement Learning: An Introducion. MIT Press, Cambridge (1998)"},{"key":"15_CR9","unstructured":"Mart\u00edn, J.D., Soria, E., Chorro, V., Climente, M., Jim\u00e9nez, N.V.: Reinforcement learning for anemia management in hemodialysis patients treated with erythropoietic stimulating factors. In: European Conference on Artificial Intelligence 2006, Proceedings of the Workshop Planning, Learning and Monitoring with uncertainty and dynamic worlds, Riva del Garda, Italy, pp. 19\u201324 (2006)"},{"key":"15_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"732","DOI":"10.1007\/978-3-540-76928-6_84","volume-title":"Twentieth Australian Joint Conference on Artificial Intelligence - AI07","author":"J.D. Mart\u00edn","year":"2007","unstructured":"Mart\u00edn, J.D., Soria, E., Mart\u00ednez, M., Climente, M., De Diego, T., Jim\u00e9nez, N.V.: Validation of a reinforcement learning policy for dosage optimization of erythropoietin. In: Orgun, M.A., Thornton, J. (eds.) AI 2007. LNCS, vol.\u00a04830, pp. 732\u2013738. Springer, Heidelberg (2007)"},{"key":"15_CR11","volume-title":"Neural Networks: A Comprehensive Foundation","author":"S. Haykin","year":"1999","unstructured":"Haykin, S.: Neural Networks: A Comprehensive Foundation, 2nd edn. Prentice Hall, Upper Saddle River (1999)","edition":"2"},{"key":"15_CR12","volume-title":"The loyalty effect: the hidden force behind growth, profits, and lasting value","author":"F.F. Reichheld","year":"2001","unstructured":"Reichheld, F.F.: The loyalty effect: the hidden force behind growth, profits, and lasting value. Harvard Business School Press, Boston (2001)"},{"key":"15_CR13","doi-asserted-by":"crossref","unstructured":"Abe, N., Verma, N., Schroko, R., Apte, C.: Cross channel optimized marketing by reinforcement learning. In: Proceedings of the KDD, pp. 767\u2013772 (2004)","DOI":"10.1145\/1014052.1016912"},{"key":"15_CR14","unstructured":"Sun, P.: Constructing Learning Models from Data: The Dynamic Catalog Mailing Problem. Ph.D thesis, Tsinghua University (2003)"},{"issue":"2","key":"15_CR15","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1002\/(SICI)1520-6653(200021)14:2<43::AID-DIR4>3.0.CO;2-H","volume":"14","author":"P.E. Pfeifer","year":"2000","unstructured":"Pfeifer, P.E., Carraway, R.L.: Modelling customer relationships as markov chains. Journal of Interactive Marketing\u00a014(2), 43\u201355 (2000)","journal-title":"Journal of Interactive Marketing"}],"container-title":["Lecture Notes in Computer Science","Recent Advances in Reinforcement Learning"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-89722-4_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,3,4]],"date-time":"2019-03-04T00:22:09Z","timestamp":1551658929000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-89722-4_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008]]},"ISBN":["9783540897217","9783540897224"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-89722-4_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2008]]}}}