{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T16:10:10Z","timestamp":1750954210291,"version":"3.41.0"},"publisher-location":"Cham","reference-count":98,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319675121"},{"type":"electronic","value":"9783319675138"}],"license":[{"start":{"date-parts":[[2017,10,20]],"date-time":"2017-10-20T00:00:00Z","timestamp":1508457600000},"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":[[2018]]},"DOI":"10.1007\/978-3-319-67513-8_7","type":"book-chapter","created":{"date-parts":[[2017,10,19]],"date-time":"2017-10-19T20:23:58Z","timestamp":1508444638000},"page":"123-160","source":"Crossref","is-referenced-by-count":8,"title":["Machine Learning Applied to Optometry Data"],"prefix":"10.1007","author":[{"given":"Beatriz","family":"Remeseiro","sequence":"first","affiliation":[]},{"given":"Noelia","family":"Barreira","sequence":"additional","affiliation":[]},{"given":"Luisa","family":"S\u00e1nchez-Brea","sequence":"additional","affiliation":[]},{"given":"Luc\u00eda","family":"Ramos","sequence":"additional","affiliation":[]},{"given":"Antonio","family":"Mosquera","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,10,20]]},"reference":[{"issue":"4","key":"7_CR1","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1016\/j.ajo.2013.12.023","volume":"157","author":"AJ Paulsen","year":"2014","unstructured":"Paulsen, A.J., Cruickshanks, K.J., Fischer, M.E., Huang, G., Klein, B.E.K., Klein, R., Dalton, D.S.: Dry eye in the beaver dam offspring study: prevalence, risk factors, and health-related quality of life. Am. J. Ophthalmol. 157(4), 799\u2013806 (2014)","journal-title":"Am. J. Ophthalmol."},{"key":"7_CR2","doi-asserted-by":"crossref","first-page":"405","DOI":"10.2147\/OPTH.S5555","volume":"3","author":"JL Gayton","year":"2009","unstructured":"Gayton, J.L.: Etiology, prevalence, and treatment of dry eye disease. Clin. Ophthalmol. 3, 405\u2013412 (2009)","journal-title":"Clin. Ophthalmol."},{"issue":"4","key":"7_CR3","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1097\/ICO.0b013e3181f7f363","volume":"30","author":"J Yu","year":"2011","unstructured":"Yu, J., Asche, C.V., Fairchild, C.J.: The economic burden of dry eye disease in the united states: a decision tree analysis. Cornea 30(4), 379\u2013387 (2011)","journal-title":"Cornea"},{"key":"7_CR4","doi-asserted-by":"crossref","unstructured":"Lemp, M.A., Baudouin, C., Baum, J., et al.: The definition and classification of dry eye disease: report of the definition and classification subcommittee of the international dry eye workshop. Ocul. Surf. 5(2), B75\u2013B92 (2007)","DOI":"10.1016\/S1542-0124(12)70081-2"},{"key":"7_CR5","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1097\/00006324-199701000-00014","volume":"74","author":"JP Craig","year":"1997","unstructured":"Craig, J.P., Tomlinson, A.: Importance of the lipid layer in human tear film stability and evaporation. Optom. Vis. Sci. 74, 8\u201313 (1997)","journal-title":"Optom. Vis. Sci."},{"issue":"Suppl 1","key":"7_CR6","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/S1367-0484(98)80035-0","volume":"21","author":"JP Guillon","year":"1998","unstructured":"Guillon, J.P.: Non-invasive tearscope plus routine for contact lens fitting. Contact Lens and Anterior Eye 21(Suppl 1), 31\u201340 (1998)","journal-title":"Contact Lens and Anterior Eye"},{"key":"7_CR7","volume-title":"The tear film: structure, function, and clinical examination","author":"DR Korb","year":"2002","unstructured":"Korb, D.R.: The Tear Film: Structure, Function, and Clinical Examination. Elsevier Health Sciences, Amsterdam (2002)"},{"issue":"6","key":"7_CR8","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1097\/00006324-200206000-00009","volume":"79","author":"JJ Nichols","year":"2002","unstructured":"Nichols, J.J., Nichols, K.K., Puent, B., Saracino, M., Mitchell, G.L.: Evaluation of tear film interference patterns and measures of tear break-up time. Optom. Vis. Sci. 79(6), 363\u2013369 (2002)","journal-title":"Optom. Vis. Sci."},{"key":"7_CR9","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1007\/978-3-642-13775-4_39","volume":"6112","author":"D Calvo","year":"2010","unstructured":"Calvo, D., Mosquera, A., Penas, M., Garc\u00eda-Res\u00faa, C., Remeseiro, B.: Color texture analysis for tear film classification: a preliminary study. Int. Conf. Image Anal. Recogn. 6112, 388\u2013397 (2010)","journal-title":"Int. Conf. Image Anal. Recogn."},{"key":"7_CR10","first-page":"66","volume":"6692","author":"L Ramos","year":"2011","unstructured":"Ramos, L., Penas, M., Remeseiro, B., Mosquera, A., Barreira, N., Yebra-Pimentel, E.: Texture and color analysis for the automatic classification of the eye lipid layer. Int. Work Conf. Artif. Neural Netw. 6692, 66\u201373 (2011)","journal-title":"Int. Work Conf. Artif. Neural Netw."},{"key":"7_CR11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2012\/207315","volume":"2012","author":"B Remeseiro","year":"2012","unstructured":"Remeseiro, B., Penas, M., Mosquera, A., Novo, J., Penedo, M.G., Yebra-Pimentel, E.: Statistical comparison of classifiers applied to the interferential tear film lipid layer automatic classification. Comput. Math. Methods Med. 2012, 1\u201310 (2012)","journal-title":"Comput. Math. Methods Med."},{"key":"7_CR12","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.cmpb.2013.04.007","volume":"111","author":"B Remeseiro","year":"2013","unstructured":"Remeseiro, B., Penas, M., Barreira, N., Mosquera, A., Novo, J., Garc\u00eda-Res\u00faa, C.: Automatic classification of the interferential tear film lipid layer using colour texture analysis. Comput. Methods Programs Biomed. 111, 93\u2013103 (2013)","journal-title":"Comput. Methods Programs Biomed."},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Remeseiro, B., Bol\u00f3n-Canedo, V., Peteiro-Barral, D., Alonso-Betanzos, A., Guijarro-Berdinas, B., Mosquera, A., Penedo, M.G., S\u00e1nchez-Marono, N.: A methodology for improving tear film lipid layer classification. IEEE J. Biomed. Health Inf. 18(4), 1485\u20131493 (2014)","DOI":"10.1109\/JBHI.2013.2294732"},{"key":"7_CR14","first-page":"732","volume":"1","author":"B Remeseiro","year":"2014","unstructured":"Remeseiro, B., Mosquera, A., Penedo, M.G., Garca-Res\u00faa, C.: Tear film maps based on the lipid interference patterns. 6th Int. Conf. Agents Artif. Int. 1, 732\u2013739 (2014)","journal-title":"6th Int. Conf. Agents Artif. Int."},{"issue":"3","key":"7_CR15","doi-asserted-by":"crossref","first-page":"936","DOI":"10.1109\/JBHI.2015.2419316","volume":"20","author":"B Remeseiro","year":"2016","unstructured":"Remeseiro, B., Mosquera, A., Penedo, M.G.: CASDES: a computer-aided system to support dry eye diagnosis based on tear film maps. IEEE J. Biomed. Health Inf. 20(3), 936\u2013943 (2016)","journal-title":"IEEE J. Biomed. Health Inf."},{"key":"7_CR16","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.cmpb.2016.02.015","volume":"130","author":"B Remeseiro","year":"2016","unstructured":"Remeseiro, B., Barreira, N., Garca-Res\u00faa, C., Lira, M., Gir\u00e1ldez, M.J., Yebra-Pimentel, E., Penedo, M.G.: iDEAS: a web-based system for dry eye assessment. Comput. Methods Prog. Biomed. 130, 186\u2013197 (2016)","journal-title":"Comput. Methods Prog. Biomed."},{"key":"7_CR17","doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez-Dom\u00ednguez, J., Remeseiro, B., Mart\u00edn, M.J.: Acceleration of tear film map definition on multicore systems. Procedia Comput. Sci. 80, 41\u201351 (2016)","DOI":"10.1016\/j.procs.2016.05.296"},{"key":"7_CR18","doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez-Dom\u00ednguez, J., Remeseiro, B., Mart\u00edn, M.J.: Parallel definition of tear film maps on distributed-memory clusters for the support of dry eye diagnosis. Comput. Methods Programs Biomed. 139, 51\u201360 (2017)","DOI":"10.1016\/j.cmpb.2016.10.027"},{"issue":"449","key":"7_CR19","first-page":"179","volume":"2014","author":"R M\u00e9ndez","year":"2014","unstructured":"M\u00e9ndez, R., Remeseiro, B., Peteiro-Barral, D., Penedo, M.G.: Evaluation of class binarization and feature selection in tear film classification using topsis. Agents Artif. Intell. Revised Selected Papers ICAART 2013 2014(449), 179\u2013193 (2014)","journal-title":"Agents Artif. Intell. Revised Selected Papers ICAART 2013"},{"issue":"4","key":"7_CR20","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1007\/s11517-016-1534-5","volume":"55","author":"D Peteiro-Barral","year":"2017","unstructured":"Peteiro-Barral, D., Remeseiro, B., M\u00e9ndez, R., Penedo, M.G.: Evaluation of an automatic dry eye test using MCDM methods and rank correlation. Med. Biol. Eng. Comput. 55(4), 527\u2013536 (2017)","journal-title":"Med. Biol. Eng. Comput."},{"key":"7_CR21","unstructured":"VOPTICAL_I1, VARPA optical dataset acquired and annotated by optometrists from the Optometry Service of the University of Santiago de Compostela, Spain (2012)"},{"key":"7_CR22","volume-title":"The image processing handbook","author":"JC Russ","year":"1999","unstructured":"Russ, J.C.: The Image Processing Handbook, 3rd edn. CRC Press Inc, Boca Raton, FL, USA (1999)","edition":"3"},{"issue":"9","key":"7_CR23","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1111\/j.1478-4408.1976.tb03301.x","volume":"92","author":"K McLaren","year":"1976","unstructured":"McLaren, K.: The development of the CIE 1976 (L*a*b) uniform colour-space and colour-difference formula. J. Soc. Dyers Colour. 92(9), 338\u2013341 (1976)","journal-title":"J. Soc. Dyers Colour."},{"key":"7_CR24","first-page":"120","volume":"25","author":"G Bradski","year":"2000","unstructured":"Bradski, G.: OpenCV. Dr. Dobb\u2019s J Softw. Tools 25, 120\u2013126 (2000)","journal-title":"Dr. Dobb\u2019s J Softw. Tools"},{"key":"7_CR25","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","volume":"3","author":"RM Haralick","year":"1973","unstructured":"Haralick, R.M., Shanmugam, K., Dinstein, I.: Texture features for image classification. IEEE Trans. Sys. Man Cybern. 3, 610\u2013621 (1973)","journal-title":"IEEE Trans. Sys. Man Cybern."},{"issue":"5","key":"7_CR26","doi-asserted-by":"crossref","first-page":"385","DOI":"10.3233\/IDA-2003-7502","volume":"7","author":"J Furnkranz","year":"2003","unstructured":"Furnkranz, J.: Round robin ensembles. Int. Data Anal. 7(5), 385\u2013403 (2003)","journal-title":"Int. Data Anal."},{"key":"7_CR27","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1613\/jair.105","volume":"2","author":"TG Dietterich","year":"1995","unstructured":"Dietterich, T.G., Bakiri, G.: Solving multiclass learning problems via error-correcting output codes. J. Artif. Intell. Res. 2, 263\u2013286 (1995)","journal-title":"J. Artif. Intell. Res."},{"key":"7_CR28","first-page":"113","volume":"1","author":"EL Allwein","year":"2001","unstructured":"Allwein, E.L., Schapire, R.E., Singer, Y.: Reducing multiclass to binary: a unifying approach for margin classifiers. J. Mach. Learn. Res. 1, 113\u2013141 (2001)","journal-title":"J. Mach. Learn. Res."},{"key":"7_CR29","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511809071","volume-title":"Introduction to information retrieval","author":"CD Manning","year":"2008","unstructured":"Manning, C.D., Raghavan, P., Sch\u00fctze, H.: Introduction to Information Retrieval, vol. 1. Cambridge University Press, Cambridge (2008)"},{"key":"7_CR30","doi-asserted-by":"crossref","unstructured":"Loughrey, J., Cunningham, P.: Overfitting in wrapper-based feature subset selection: the harder you try the worse it gets. Res. Dev. Intell. Sys. XXI, 2005, 33\u201343 (2005)","DOI":"10.1007\/1-84628-102-4_3"},{"key":"7_CR31","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-540-35488-8","volume-title":"Feature Extraction: Foundations and Applications","author":"I Guyon","year":"2006","unstructured":"Guyon, I., Gunn, S., Nikravesh, M., Zadeh, L.: Feature Extraction: Foundations and Applications. Springer Verlag, Berlin (2006)"},{"key":"7_CR32","unstructured":"Hall, M.A.: Correlation-based feature selection for machine learning. PhD thesis, The University of Waikato (1999)"},{"issue":"1\u20132","key":"7_CR33","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/S0004-3702(03)00079-1","volume":"151","author":"M Dash","year":"2003","unstructured":"Dash, M., Liu, H.: Consistency-based search in feature selection. Artif. Intell. 151(1\u20132), 155\u2013176 (2003)","journal-title":"Artif. Intell."},{"key":"7_CR34","unstructured":"Zhao, Z., Liu, H.: Searching for interacting features. Proceedings of the 20th international joint conference on Artificial intelligence, 1156\u20131161 (2007)"},{"key":"7_CR35","volume-title":"Machine Learning","author":"TM Mitchell","year":"1995","unstructured":"Mitchell, T.M.: Machine Learning. McGraw-Hill, Boston (1995)"},{"key":"7_CR36","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1080\/01621459.1989.10478752","volume":"84","author":"JH Friedman","year":"1989","unstructured":"Friedman, J.H.: Regularized discriminant analysis. J. Am. Stat. Assoc. 84, 165\u2013175 (1989)","journal-title":"J. Am. Stat. Assoc."},{"key":"7_CR37","unstructured":"Jensen, F.V.: An Introduction to Bayesian Networks, vol. 210. UCL press, London (1996)"},{"key":"7_CR38","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1023\/A:1009744630224","volume":"2","author":"SK Murthy","year":"1998","unstructured":"Murthy, S.K.: Automatic construction of decision trees from data: a multi-disciplinary survey. Data Min. Knowl. Disc. 2, 345\u2013389 (1998)","journal-title":"Data Min. Knowl. Disc."},{"key":"7_CR39","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1023\/A:1009715923555","volume":"2","author":"CJC Burges","year":"1998","unstructured":"Burges, C.J.C.: A tutorial on support vector machines for pattern recognition. Data Min. Knowl. Disc. 2, 121\u2013167 (1998)","journal-title":"Data Min. Knowl. Disc."},{"issue":"6","key":"7_CR40","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1037\/h0042519","volume":"65","author":"F Rosenblatt","year":"1958","unstructured":"Rosenblatt, F.: The perceptron: a probabilistic model for information storage and organization in the brain. Psychol. Rev. 65(6), 386 (1958)","journal-title":"Psychol. Rev."},{"issue":"5","key":"7_CR41","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1109\/TNN.2010.2041468","volume":"21","author":"JC Fernandez-Caballero","year":"2010","unstructured":"Fernandez-Caballero, J.C., Martnez, F.J., Herv\u00e1s, C., Guti\u00e9rrez, P.A.: Sensitivity versus accuracy in multiclass problems using memetic pareto evolutionary neural networks. IEEE Trans. Neural Networks 21(5), 750\u2013770 (2010)","journal-title":"IEEE Trans. Neural Networks"},{"key":"7_CR42","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-48318-9","volume-title":"Multiple attribute decision making: methods and applications","author":"CL Hwang","year":"1981","unstructured":"Hwang, C.L., Yoon, K.: Multiple Attribute Decision Making: Methods and Applications, vol. 13. Springer-Verlag, New York (1981)"},{"issue":"1","key":"7_CR43","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.cie.2007.12.002","volume":"55","author":"Y Kuo","year":"2008","unstructured":"Kuo, Y., Yang, T., Huang, G.W.: The use of grey relational analysis in solving multiple attribute decision-making problems. Comput. Ind. Eng. 55(1), 80\u201393 (2008)","journal-title":"Comput. Ind. Eng."},{"issue":"1","key":"7_CR44","first-page":"5","volume":"2","author":"S Opricovic","year":"1998","unstructured":"Opricovic, S.: Multicriteria optimization of civil engineering systems. Fac. Civil Eng. Belgrade 2(1), 5\u201321 (1998)","journal-title":"Fac. Civil Eng. Belgrade"},{"issue":"4","key":"7_CR45","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1080\/713848278","volume":"2","author":"TD Gautheir","year":"2001","unstructured":"Gautheir, T.D.: Detecting trends using spearman\u2019s rank correlation coefficient. Environ. Forensics 2(4), 359\u2013362 (2001)","journal-title":"Environ. Forensics"},{"key":"7_CR46","doi-asserted-by":"crossref","unstructured":"Chang, C., Lin, C.: LIBSVM: A library for support vector machines. ACM Trans. on Intell. Sys. Tech. 2, 1\u201327, http:\/\/www.csie.ntu.edu.tw\/cjlin\/libsvm (2011)","DOI":"10.1145\/1961189.1961199"},{"key":"7_CR47","volume-title":"Principles of data mining","author":"M Bramer","year":"2007","unstructured":"Bramer, M.: Principles of Data Mining, vol. 180. Springer, London (2007)"},{"issue":"1","key":"7_CR48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10384-011-0107-2","volume":"56","author":"T Yoneda","year":"2012","unstructured":"Yoneda, T., Sumi, T., Takahashi, A., Hoshikawa, Y., Kobayashi, M., Fukushima, A.: Automated hyperemia analysis software: reliability and reproducibility in healthy subjects. Jpn. J. Ophthalmol. 56(1), 1\u20137 (2012)","journal-title":"Jpn. J. Ophthalmol."},{"key":"7_CR49","doi-asserted-by":"crossref","first-page":"1197","DOI":"10.2147\/OPTH.S39703","volume":"7","author":"JD Rodriguez","year":"2013","unstructured":"Rodriguez, J.D., Johnston, P.R., Ousler, G.W., Smith, L.M., Abelson, M.B.: Automated grading system for evaluation of ocular redness associated with dry eye. Clin. Ophthalmol. 7, 1197 (2013)","journal-title":"Clin. Ophthalmol."},{"issue":"8","key":"7_CR50","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1097\/OPX.0000000000000643","volume":"92","author":"S Wu","year":"2015","unstructured":"Wu, S., Hong, J., Tian, L., Cui, X., Sun, X., Xu, J.: Assessment of bulbar redness with a newly developed keratograph. Optom. Vis. Sci. 92(8), 892\u2013899 (2015)","journal-title":"Optom. Vis. Sci."},{"key":"7_CR51","first-page":"5","volume":"2","author":"M Tort","year":"2012","unstructured":"Tort, M., Ornberg, R., Lay, B., Danno, R., Soong, F., Salapatek, A.: Development of an objective assessment of conjunctival hyperemia elicited via Conjunctival Allergen Provocation Testing (CAPT) and Environmental Exposure Chamber (EEC) testing. EEC (N\u00a0=\u00a013) 2, 5 (2012)","journal-title":"EEC (N\u00a0=\u00a013)"},{"key":"7_CR52","first-page":"12300","volume":"56","author":"MJ Wald","year":"2015","unstructured":"Wald, M.J., Lay, B., Danno, R., Grosskreutz, C.L., Chandra, S.: Performance of automated hyperemia assessment in allergic conjunctivitis interventional study. Invest. Ophthalmol. Vis. Sci. 56, 12300 (2015)","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"issue":"2","key":"7_CR53","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1111\/opo.12245","volume":"36","author":"LE Downie","year":"2016","unstructured":"Downie, L.E., Keller, P.R., Vingrys, A.J.: Assessing ocular bulbar redness: a comparison of methods. Ophthalmic Physiol. Opt. 36(2), 132\u2013139 (2016)","journal-title":"Ophthalmic Physiol. Opt."},{"issue":"7","key":"7_CR54","doi-asserted-by":"crossref","first-page":"4821","DOI":"10.1167\/iovs.13-12217","volume":"54","author":"F Amparo","year":"2013","unstructured":"Amparo, F., Wang, H., Emami-Naeini, P., Karimian, P., Dana, R.: The ocular redness index: a novel automated method for measuring ocular injectiona novel automated system to measure redness. Invest. Ophthalmol. Vis. Sci. 54(7), 4821\u20134826 (2013)","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"issue":"3","key":"7_CR55","first-page":"687","volume":"41","author":"EB Papas","year":"2000","unstructured":"Papas, E.B.: Key factors in the subjective and objective assessment of conjunctival erythema. Invest. Ophthalmol. Vis. Sci. 41(3), 687\u2013691 (2000)","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"issue":"1","key":"7_CR56","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/S1367-0484(02)00062-0","volume":"26","author":"JS Wolffsohn","year":"2003","unstructured":"Wolffsohn, J.S., Purslow, C.: Clinical monitoring of ocular physiology using digital image analysis. Contact Lens and Anterior Eye 26(1), 27\u201335 (2003)","journal-title":"Contact Lens and Anterior Eye"},{"issue":"1","key":"7_CR57","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1046\/j.1475-1313.1999.00420.x-i1","volume":"21","author":"N Efron","year":"2001","unstructured":"Efron, N., Morgan, P.B., Katsara, S.S.: Validation of grading scales for contact lens complications. Ophthalmic Physiol. Opt. 21(1), 17\u201329 (2001)","journal-title":"Ophthalmic Physiol. Opt."},{"issue":"2","key":"7_CR58","first-page":"340","volume":"43","author":"P Fieguth","year":"2002","unstructured":"Fieguth, P., Simpson, T.: Automated measurement of bulbar redness. Invest. Ophthalmol. Vis. Sci. 43(2), 340\u2013347 (2002)","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"issue":"5","key":"7_CR59","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1038\/sj.eye.6702295","volume":"21","author":"PJ Murphy","year":"2007","unstructured":"Murphy, P.J., Lau, J.S.C., Sim, M.M.L., Woods, R.L.: How red is a white eye? Clinical grading of normal conjunctival hyperemia. Eye 21(5), 633\u2013638 (2007)","journal-title":"Eye"},{"issue":"11","key":"7_CR60","doi-asserted-by":"crossref","first-page":"1434","DOI":"10.1136\/bjo.2004.045534","volume":"88","author":"JS Wolffsohn","year":"2004","unstructured":"Wolffsohn, J.S.: Incremental nature of anterior eye grading scales determined by objective image analysis. Br. J. Ophthalmol. 88(11), 1434\u20131438 (2004)","journal-title":"Br. J. Ophthalmol."},{"key":"7_CR61","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez, L., Barreira, N., Pena-Verdeal, H., Yebra-Pimentel, E.: A Novel Framework for Hyperemia Grading Based on Artificial Neural Networks, pp.\u00a0263\u2013275. Springer, Heidelberg (2015)","DOI":"10.1007\/978-3-319-19258-1_23"},{"key":"7_CR62","doi-asserted-by":"crossref","first-page":"103411T","DOI":"10.1117\/12.2268804","volume":"10341","author":"L S\u00e1nchez","year":"2017","unstructured":"S\u00e1nchez, L., Barreira, N., S\u00e1nchez, N., Mosquera, A., Pena-Verdeal, H., Yebra-Pimentel, E.: On the analysis of local and global features for hyperemia grading. Ninth Int. Conf. Mach. Vis. 10341, 103411T\u2013103411T (2017)","journal-title":"Ninth Int. Conf. Mach. Vis."},{"key":"7_CR63","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez-Brea, M.L., Barreira-Rodrguez, N., Mosquera-Gonz\u00e1lez, A., Evans, K., Pena-Verdeal, H.: Defining the optimal region of interest for hyperemia grading in the bulbar conjunctiva. Comput. Math. Methods Med. 2016, 1\u20139 (2016)","DOI":"10.1155\/2016\/3695014"},{"key":"7_CR64","doi-asserted-by":"crossref","unstructured":"V\u00e1zquez, S.G., Barreira, N., Penedo, M.G., Pena-Seijo, M., G\u00f3mez-Ulla, F.: Evaluation of SIRIUS retinal vessel width measurement in REVIEW dataset. IEEE 26th Int. Symp. Comp. Med. Syst. 2013, 71\u201376 (2013)","DOI":"10.1109\/CBMS.2013.6627767"},{"key":"7_CR65","unstructured":"Robnik-\u0160ikonja, M., Kononenko, I.: An adaptation of Relief for attribute estimation in regression. In Machine Learning: Proceedings of the Fourteenth International Conference, 296\u2013304 (1997)"},{"key":"7_CR66","first-page":"343","volume":"92","author":"JR Quinlan","year":"1992","unstructured":"Quinlan, J.R.: Learning with continuous classes. Aust. Jt Conf. Artif. Intell. 92, 343\u2013348 (1992)","journal-title":"Aust. Jt Conf. Artif. Intell."},{"issue":"5","key":"7_CR67","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.1109\/72.870050","volume":"11","author":"SK Shevade","year":"2000","unstructured":"Shevade, S.K., Keerthi, S.S., Bhattacharyya, C., Murthy, K.R.K.: Improvements to the SMO algorithm for SVM regression. IEEE Trans. Neural Netw. 11(5), 1188\u20131193 (2000)","journal-title":"IEEE Trans. Neural Netw."},{"issue":"1\u20133","key":"7_CR68","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1023\/A:1012487302797","volume":"46","author":"I Guyon","year":"2002","unstructured":"Guyon, I., Weston, J., Barnhill, S., Vapnik, V.: Gene selection for cancer classification using support vector machines. Mach. Learn. 46(1\u20133), 389\u2013422 (2002)","journal-title":"Mach. Learn."},{"key":"7_CR69","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez-Brea, M.L., Barreira, N., S\u00e1nchez-Maro\u00f1o, N., Mosquera, A., Garc\u00eda-Res\u00faa, C., Gir\u00e1ldez-Fern\u00e1ndez, M.J.: On the development of conjunctival hyperemia computer-assisted diagnosis tools: Influence of feature selection and class imbalance in automatic gradings. Artif. Intell. Med. 71, 30\u201342 (2016)","DOI":"10.1016\/j.artmed.2016.06.004"},{"key":"7_CR70","first-page":"423","volume":"2","author":"L Sanchez","year":"2016","unstructured":"Sanchez, L., Barreira, N., Mosquera, A., Pena-Verdeal, H., Yebra-Pimentel, E.: Comparing machine learning techniques in a hyperemia grading framework. Int. Conf. Agents Artif. Intell. 2, 423\u2013429 (2016)","journal-title":"Int. Conf. Agents Artif Intell"},{"issue":"3","key":"7_CR71","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/0885-064X(88)90020-9","volume":"4","author":"EB Baum","year":"1988","unstructured":"Baum, E.B.: On the capabilities of multilayer perceptrons. J Complexity 4(3), 193\u2013215 (1988)","journal-title":"J Complexity"},{"issue":"2","key":"7_CR72","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1162\/neco.1991.3.2.246","volume":"3","author":"J Park","year":"1991","unstructured":"Park, J., Sandberg, I.W.: Universal approximation using radial-basis-function networks. Neural Comput. 3(2), 246\u2013257 (1991)","journal-title":"Neural Comput."},{"issue":"1\u20133","key":"7_CR73","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0925-2312(98)00030-7","volume":"21","author":"T Kohonen","year":"1998","unstructured":"Kohonen, T.: The self-organizing map. Neurocomputing 21(1\u20133), 1\u20136 (1998)","journal-title":"Neurocomputing"},{"key":"7_CR74","doi-asserted-by":"crossref","unstructured":"Kohonen, T.: Improved versions of learning vector quantization. Int. Jt Conf. Neural Netw. 1990, 545\u2013550 (1990)","DOI":"10.1109\/IJCNN.1990.137622"},{"issue":"1","key":"7_CR75","first-page":"81","volume":"1","author":"JR Quinlan","year":"1986","unstructured":"Quinlan, J.R.: Induction of decision trees. Mach. Learn. 1(1), 81\u2013106 (1986)","journal-title":"Mach. Learn."},{"issue":"1","key":"7_CR76","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"issue":"3","key":"7_CR77","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1023\/B:STCO.0000035301.49549.88","volume":"14","author":"AJ Smola","year":"2004","unstructured":"Smola, A.J., Sch\u00f6lkopf, B.: A tutorial on support vector regression. Stat. Comput. 14(3), 199\u2013222 (2004)","journal-title":"Stat. Comput."},{"issue":"4","key":"7_CR78","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1109\/TSMC.1976.5408784","volume":"6","author":"SA Dudani","year":"1976","unstructured":"Dudani, S.A.: The distance-weighted k-nearest-neighbor rule. IEEE Trans. Syst. Man Cybern. 6(4), 325\u2013327 (1976)","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"7_CR79","unstructured":"Abdi, H.: Partial least square regression (PLS regression). Encycl. Res. Methods Soc. Sci. 6(4), 792\u2013795, 2003"},{"key":"7_CR80","unstructured":"John, G.H., Langley, P.: Estimating continuous distributions in bayesian classifiers.Conf. Uncertainty Artif. Intell. 1995, 338\u2013345, (1995)"},{"key":"7_CR81","doi-asserted-by":"crossref","unstructured":"Abelson, M.B., Ousler, G.W., Nally, L.A., Welch, D., Krenzer, K.: Alternative reference values for tear film break up time in normal and dry eye Populations. In Lacrimal Gland, Tear Film, and Dry Eye Syndromes 3, pp.\u00a01121\u20131125. Springer, New York (2002)","DOI":"10.1007\/978-1-4615-0717-8_157"},{"key":"7_CR82","doi-asserted-by":"crossref","unstructured":"King-Smith, P.E., Fink, B.A., Nichol J.J., Braun, R.J., McFadden, G.B.: The contribution of lipid layer movement to tear film thinning and breakup. Invest. Opthalmol. Vis. Sci. 50, 2747\u20132756 (2009)","DOI":"10.1167\/iovs.08-2459"},{"key":"7_CR83","doi-asserted-by":"crossref","unstructured":"Bitton, E., Lovasik, J. V.: Longitudinal analysis of precorneal tear film rupture patterns. In Lacrimal Gland, Tear Film, and Dry Eye Syndromes 2, pp.\u00a0381\u2013389. Springer, New York (1998)","DOI":"10.1007\/978-1-4615-5359-5_53"},{"key":"7_CR84","doi-asserted-by":"crossref","unstructured":"Yedidya,T., Hartley, R., Guillon, J.P.: Automatic detection of pre-ocular tear film break-up sequence in dry eyes. Digit. Image Comput. Tech. and Appl., 2008, 442\u2013448 (2008)","DOI":"10.1109\/DICTA.2008.70"},{"key":"7_CR85","doi-asserted-by":"crossref","unstructured":"Cebreiro, E., Ramos, L., Mosquera, A., Barreira, N., Penedo, M.G.: Automation of the tear film break-up time test. Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, 123 (2011)","DOI":"10.1145\/2093698.2093821"},{"key":"7_CR86","doi-asserted-by":"crossref","unstructured":"Ramos, L., Barreira, N., Mosquera, A., Curr\u00e1s, M., Pena-Verdeal, H. Gir\u00e1ldez, M.J., Penedo, M.G: Adaptive parameter computation for the automatic measure of the Tear Break-Up Time. 16th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 243, 1370\u20131379 (2012)","DOI":"10.3233\/978-1-61499-105-2-1370"},{"issue":"3","key":"7_CR87","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1016\/j.cmpb.2013.12.003","volume":"113","author":"L Ramos","year":"2014","unstructured":"Ramos, L., Barreira, N., Mosquera, A., Penedo, M.G., Yebra-Pimentel, E., Garc\u00eda-Res\u00faa, C.: Analysis of parameters for the automatic computation of the tear film break-up time test based on cclru standards. Comput. Methods Programs Biomed. 113(3), 715\u2013724 (2014)","journal-title":"Comput. Methods Programs Biomed."},{"key":"7_CR88","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.biosystemseng.2015.04.009","volume":"138","author":"L Ramos","year":"2015","unstructured":"Ramos, L., Barreira, N., Pena-Verdeal, H., Gir\u00e1ldez, M.J., Yebra-Pimentel, E.: Computational approach for tear film assessment based on break-up dynamics. Biosys. Eng. 138, 90\u2013103 (2015)","journal-title":"Biosys. Eng."},{"key":"7_CR89","doi-asserted-by":"crossref","unstructured":"Ramos, L., Barreira, N., Mosquera, A., Pena-Verdeal, H., Yebra-Pimentel, E.: Break-up analysis of the tear film based on time, location, size and shape of the rupture area. International Conference Image Analysis and Recognition, 695\u2013702 (2013)","DOI":"10.1007\/978-3-642-39094-4_79"},{"issue":"3","key":"7_CR90","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.media.2004.07.001","volume":"9","author":"M Foracchia","year":"2005","unstructured":"Foracchia, M., Grisan, E., Ruggeri, A.: Luminosity and contrast normalization in retinal images. Med. Image Anal. 9(3), 179\u2013190 (2005)","journal-title":"Med. Image Anal."},{"issue":"2","key":"7_CR91","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.patrec.2007.09.005","volume":"29","author":"S Arora","year":"2008","unstructured":"Arora, S., Acharya, J., Verma, A., Prasanta, K.: Panigrahi. Multilevel thresholding for image segmentation through a fast statistical recursive algorithm. Pattern Recogn. Lett. 29(2), 119\u2013125 (2008)","journal-title":"Pattern Recogn. Lett."},{"key":"7_CR92","volume-title":"An introduction to morphological image processing","author":"ER Dougherty","year":"1992","unstructured":"Dougherty, E.R.: An introduction to morphological image processing. SPIE Optical Engineering Press, Tutorial texts in optical engineering (1992)"},{"issue":"1","key":"7_CR93","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/0734-189X(85)90016-7","volume":"30","author":"S Suzuki","year":"1985","unstructured":"Suzuki, S., Abe, K.: Topological structural analysis of digitized binary images by border following. Comput. Vis. Graph. Image Process. 30(1), 32\u201346 (1985)","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"7_CR94","first-page":"179","volume":"8","author":"M Hu","year":"1962","unstructured":"Hu, M.: Visual pattern recognition by moment invariants, computer methods in image analysis. IRE Trans. Inf. Theory 8, 179\u2013187 (1962)","journal-title":"IRE Trans. Inf. Theory"},{"issue":"8","key":"7_CR95","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1364\/JOSA.70.000920","volume":"70","author":"M Reed-Teague","year":"1980","unstructured":"Reed-Teague, M.: Image analysis via the general theory of moments. J. Opt. Soc. Am. 70(8), 920\u2013930 (1980)","journal-title":"J. Opt. Soc. Am."},{"key":"7_CR96","unstructured":"Nunes, J.F., Moreira, P.M., Tavares, J.M.R.S: Shape based image retrieval and classification. 5th Iberian Conference on Information Systems and Technologies (2010)"},{"issue":"3","key":"7_CR97","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1109\/TPAMI.2009.187","volume":"32","author":"J Rodriguez","year":"2010","unstructured":"Rodriguez, J., Perez, A., Lozano, J.: Sensitivity analysis of k-fold cross validation in prediction error estimation. IEEE Trans. Pattern Anal. Mach. Intell. 32(3), 569\u2013575 (2010)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"7_CR98","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-1904-8","volume-title":"Principal Component Analysis","author":"IT Jolliffe","year":"1986","unstructured":"Jolliffe, I.T.: Principal Component Analysis. Springer Verlag, New York (1986)"}],"container-title":["Intelligent Systems Reference Library","Advances in Biomedical Informatics"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-67513-8_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T15:43:37Z","timestamp":1750952617000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-67513-8_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,20]]},"ISBN":["9783319675121","9783319675138"],"references-count":98,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-67513-8_7","relation":{},"ISSN":["1868-4394","1868-4408"],"issn-type":[{"type":"print","value":"1868-4394"},{"type":"electronic","value":"1868-4408"}],"subject":[],"published":{"date-parts":[[2017,10,20]]}}}