Novel approach for fetal heart rate classification introducing grammatical evolution

Carter, 1993, Present day performance qualities of cardiotocographs, Br. J. Obstet. Gynaecol., 100, 10, 10.1111/j.1471-0528.1993.tb10628.x Geijn, 1996, Developments in CTG analysis, Bailliere's Clin. Obstet. Gynaecol., 10, 185, 10.1016/S0950-3552(96)80033-2 MacDonald, 1985, The Dublin randomized controlled trial of intrapartum fetal heart rate monitoring, Am. J. Obstet. Gynaecol., 152, 524, 10.1016/0002-9378(85)90619-2 Bernardes, 1997, Evaluation of interobserver agreement of cardiotocograms, Int. J. Gynaecol. Obstet., 57, 33, 10.1016/S0020-7292(97)02846-4 Ayres-de-Campos, 1999, Inconsistencies in classification by expert of cardiotocograms and subsequent clinical decision, Br. J. Obstet. Gynaecol., 106, 1307, 10.1111/j.1471-0528.1999.tb08187.x Signorini, 2003, Linear and nonlinear parameters for the analysis of fetal heart rate signal from cardiotocographic recordings, IEEE Trans. Biomed. Eng., 50, 365, 10.1109/TBME.2003.808824 Arduini, 1993, Computerized analysis of fetal heart rate: I. Description of the system (2CTG), J. Matern. Fetal Invest., 3, 159 Mantel, 1990, Computer analysis of antepartum fetal heart rate: 1. Baseline determination, Int. J. Biomed. Comput., 25, 261, 10.1016/0020-7101(90)90030-X Mantel, 1990, Computer analysis of antepartum fetal heart rate: 2. Detection of accelerations and decelerations, Int. J. Biomed. Comput., 25, 273, 10.1016/0020-7101(90)90031-O Mongelli, 1997, Computerized estimation of the baseline fetal heart rate in labour: the low frequency line, Br. J. Obstet. Gynaecol., 104, 1128, 10.1111/j.1471-0528.1997.tb10935.x Taylor, 2000, The development and validation of an algorithm for real time computerized fetal heart rate monitoring in labour, Br. J. Obstet. Gynaecol., 107, 1130, 10.1111/j.1471-0528.2000.tb11112.x Dawes, 1995, Computerized analysis of antepartum fetal heart rate, Am. J. Obstet. Gynaecol., 173, 1353, 10.1016/0002-9378(95)91391-2 Jezewski, 1993, Fetal monitoring with automated analysis of cardiotocogram: the KOMPOR system, 638 Maeda, 1990, Computerized analysis of cardiotocograms and fetal movements, Bailliere's Clin. Obstet. Gynaecol., 4, 797, 10.1016/S0950-3552(05)80345-1 Ulbricht, 1998, Neural networks for recognizing patterns in cardiotocograms, Artif. Intell. Med., 12, 271, 10.1016/S0933-3657(97)00052-3 Fontenla-Romero, 2001, Adaptive pattern recognition in the analysis of cardiotocographic records, IEEE Trans. Neural Netw., 12, 1188, 10.1109/72.950146 Bernardes, 1991, The Porto system for automated cardiotocographic signal analysis, J. Perinat. Med., 19, 61, 10.1515/jpme.1991.19.1-2.61 Bernardes, 1994, The Porto system, 315 Ayres-de-Campos, 2000, SisPorto 2.0: a program for automated analysis of cardiotocograms, J. Matern. Fetal Med., 9, 311, 10.1002/1520-6661(200009/10)9:5<311::AID-MFM12>3.0.CO;2-9 Magenes, 2000, Classification of cardiotocographic records by neural networks, 637 Magenes, 2001, Multiparametric analysis of fetal heart rate: comparison of neural and statistical methods, Proc. Medicon Kol, 1995, Interpretation of nonstress tests by an artificial neural network, Am. J. Obstet. Gynaecol., 172, 1372, 10.1016/0002-9378(95)90465-4 Chung, 1995, The prediction of fetal acidosis at birth by computerized analysis of intrapartum cardiotocography, Br. J. Obstet. Gynaecol., 102, 454, 10.1111/j.1471-0528.1995.tb11317.x Salamalekis, 2002, Computerised intrapartum diagnosis of fetal hypoxia based on fetal heart rate monitoring and fetal pulse oximetry recordings utilising wavelet analysis and neural networks, Br. J. Obstet. Gynaecol., 109, 1137, 10.1111/j.1471-0528.2002.01388.x Z.R. Struzik, W.J. Wijngaarden, Cumulative effective Hölder exponent based indicator for real time fetal heartbeat analysis during labour, Report INS-R0110 2001. Georgoulas, 2006, Feature extraction and classification of Fetal Heart Rate using Wavelet analysis and Support Vector Machines, Int. J. AI Tools, 15, 411, 10.1142/S0218213006002746 Ifeachor, 1991, An expert system to assist in the management of labour, 2615 Skinner, 1999, A fuzzy system for fetal heart rate assessment, 20 Alonso-Betanzos, 1992, Computerized antenatal assessment: The NST-EXPERT project, Automedica, 14, 3 Alonso-Betanzos, 1995, The NST-EXPERT project: the need to evolve, Artif. Intell. Med., 7, 297, 10.1016/0933-3657(95)00007-S Guijarro-Berdinas, 2002, Intelligent analysis and pattern recognition in cardiotocographic signals using a tightly coupled hybrid system, Artif. Intell., 136, 1, 10.1016/S0004-3702(01)00163-1 Haykin, 1999 Bishop, 1995 Georgoulas, 2004, Classification of cardiotocograms using Support Vector Machines Georgoulas, 2006, Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines, IEEE Trans. Biomed. Eng., 53, 875, 10.1109/TBME.2006.872814 O’Neill, 2001, Grammatical Evolution, IEEE Trans. Evol. Comput., 5, 349, 10.1109/4235.942529 Koza, 1992 Naur, 1963, Revised Report on the Algorithmic Language ALGOL 60, Commun. ACM, 6, 1, 10.1145/366193.366201 I.G. Tsoulos, D. Gavrilis, E. Dermatas, Features Selection and Construction using Grammatical Evolution, submitted to IEEE Transactions on Evolutionary Computation. Theodoridis, 2006 Kohavi, 1997, Wrappers for feature subset selection, Artif. Intell., 97, 273, 10.1016/S0004-3702(97)00043-X Sa, 2001 Rooth, 1987, Guidelines for the use of fetal monitoring, Int. J. Gynaecol. Obstet., 25, 159 National Institute of Child Health and Human Development Research Planning Workshop, Electronic fetal heart rate monitoring: research guidelines for interpretation, Am. J. Obstet. Gynaecol. 177 (6) (1997) 1385–1390. Goncalves, 2006, Internal versus external intrapartum foetal heart rate monitoring: the effect on linear and nonlinear parameters, Physiol. Meas., 27, 307, 10.1088/0967-3334/27/3/008 Chawla, 2004, Editorial: special issue on learning from imbalanced data sets, SIGKDD Explor., 6, 1, 10.1145/1007730.1007733 Chawla, 2002, SMOTE: Synthetic Minority Over-Sampling Technique, J. Artif. Intell. Res., 16, 3241, 10.1613/jair.953 Powell, 1989, A tolerant algorithm for linearly constrained optimization calculations, Math. Program., 45, 547, 10.1007/BF01589118 Haupt, 2004 Breiman, 1984 Salzberg, 1997, On comparing classifiers: pitfalls to avoid and a recommended approach, Data Min. Know. Disc., 1, 317, 10.1023/A:1009752403260 Duda, 2001 Provost, 1997, Analysis and visualization of classifier performance: comparison under imprecise class and cost distribution, 43 A. Flexer, Statistical evaluation of neural network experiments: minimum requirements and current practice, Technical Report, The Austrian Research Institute of Artificial Intelligence, 1994. Burrell, 2007, Feature analysis of functional MRI for discrimination between normal and epileptogenic brain, 2554 O. Smart, H. Firpi, G. Vachtsevanos, Genetic programming of conventional features to detect seizure precursors, Engineering Applications of Artificial Intelligence, in press. Amer-Wahlin, 2001, Cardiotocography only versus cardiotocography plus ST analysis of fetal electrocardiogram for intrapartum fetal monitoring: a Swedish randomised controlled trial, Lancet, 358, 534, 10.1016/S0140-6736(01)05703-8 Rosén, 2001, Intrapartum fetal monitoring and the fetal ECG—time for a change, Arch. Perinat. Med., 7, 7 Bernardes, 1998, Objective computerized fetal heart rate analysis, Int. J. Gynaecol. Obstet., 62, 141, 10.1016/S0020-7292(98)00079-4