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Mathematical Methods of Signal Analysis Applied in Medical Diagnostic

International Journal of Applied Mathematics and Computer Science's Cover Image
International Journal of Applied Mathematics and Computer Science
Big Data and Signal Processing (Special section, pp. 399-473), Joanna Kołodziej, Sabri Pllana, Salvatore Vitabile (Eds.)

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Anderson, P.B. and Rogers, M.H. (2009). Deep Brain Stimulation: Applications, Complications and Side Effects, Nova Biomedical Books, New York, NY.Search in Google Scholar

Apostolidis-Afentoulis, V. and Lioufi, K.I. (2015). classification with linear and RBF kernels, http://www.academia.edu/13811676/SVM_Classification_with_Linear_and_RBF_kernels.Search in Google Scholar

Cagnan, H., Dolan, K., He, X., Contarino, M.F., Schuurman, R., Van Den Munckhof, P., Wadman, W.J., Bour, L. and Martens, H.C. (2011). Automatic subthalamic nucleus detection from microelectrode recordings based on noise level and neuronal activity, Journal of Neural Engineering8(4): 046006.10.1088/1741-2560/8/4/04600621628771Search in Google Scholar

Ciecierski, K.A., Raś, Z.W. and Przybyszewski, A.W. (2014a). Foundations of automatic system for intrasurgical localization of subthalamic nucleus in Parkinson patients, Web Intelligence and Agent Systems12(1): 63–82.10.3233/WIA-140286Search in Google Scholar

Ciecierski, K., Mandat, T., Rola, R., Raś, Z.W. and Przybyszewski, A.W. (2014b). Computer aided subthalamic nucleus (STN) localization during deep brain stimulation (DBS) surgery in Parkinson’s patients, Annales Academiae Medicae Silesiensis5(68): 275–283.Search in Google Scholar

Dietterich, T.G. (2000). Ensemble methods in machine learning, in J. Kittler and F. Rodi (Eds), Multiple Classifier Systems, Springer, Berlin, pp. 1–15, DOI: 10.1007/3-540-45014-9_1.10.1007/3-540-45014-9_1Search in Google Scholar

Duch, W., Adamczak, R. and Diercksen, G.H.F. (2000). Classification, association and pattern completion using neural similarity based methods, International Journal of Applied Mathematics and Computer Science10(4): 747–766.Search in Google Scholar

Freeman, E.A. and Moisen, G.G. (2008). A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappa, Ecological Modelling217(1–2): 48–58.10.1016/j.ecolmodel.2008.05.015Search in Google Scholar

Ho, A.L., Ali, R., Connolly, I.D., Henderson, J.M., Dhall, R., Stein, S.C. and Halpern, C.H. (2018). Awake versus asleep deep brain stimulation for Parkinson’s disease: A critical comparison and meta-analysis, Journal of Neurology, Neurosurgery & Psychiatry89(7): 687–691.10.1136/jnnp-2016-31450028250028Search in Google Scholar

Hutchison, W.D., Allan, R.J., Opitz, H., Levy, R., Dostrovsky, J.O., Lang, A.E. and Lozano, A.M. (1998). Neurophysiological identification of the subthalamic nucleus in surgery for Parkinson’s disease, Annals of Neurology44(4): 622–628.10.1002/ana.4104404079778260Search in Google Scholar

Israel, Z. and Burchiel, K.J. (2011). Microelectrode Recording in Movement Disorder Surgery, Thieme, Stuttgart.Search in Google Scholar

Jeleń, Ł., Fevens, T. and Krzyżak, A. (2008). Classification of breast cancer malignancy using cytological images of fine needle aspiration biopsies, International Journal of Applied Mathematics and Computer Science18(1): 75–83, DOI: 10.2478/v10006-008-0007-x.10.2478/v10006-008-0007-xSearch in Google Scholar

Jensen, A. and la Cour-Harbo, A. (2001). Ripples in Mathematics: The Discrete Wavelet Transform, Berlin/Heidelberg.10.1007/978-3-642-56702-5Search in Google Scholar

Kano, T., Katayama, Y., Kobayashi, K., Kasai, M., Oshima, H., Fukaya, C. and Yamamoto, T. (2006). Detection of boundaries of subthalamic nucleus by multiple-cell spike density analysis in deep brain stimulation for Parkinson’s disease, in J.W. Chang et al. (Eds), Advances in Functional and Reparative Neurosurgery, Springer, Vienna, pp. 33–35.10.1007/978-3-211-35205-2_617370760Search in Google Scholar

Koch, C. (2004). Biophysics of Computation: Information Processing in Single Neurons, Oxford University Press, Oxford.Search in Google Scholar

Levy, R., Hutchison, W.D., Lozano, A.M. and Dostrovsky, J.O. (2000). High-frequency synchronization of neuronal activity in the subthalamic nucleus of parkinsonian patients with limb tremor, Journal of Neuroscience20(20): 7766–7775.10.1523/JNEUROSCI.20-20-07766.2000Search in Google Scholar

Lewicki, M.S. (1998). A review of methods for spike sorting: The detection and classification of neural action potentials, Network: Computation in Neural Systems9(4): R53–R78.10.1088/0954-898X_9_4_001Search in Google Scholar

Mallet, L., Schüpbach, M., N’Diaye, K., Remy, P., Bardinet, E., Czernecki, V., Welter, M.-L., Pelissolo, A., Ruberg, M., Agid, Y. and Yelnik, J. (2007). Stimulation of subterritories of the subthalamic nucleus reveals its role in the integration of the emotional and motor aspects of behavior, Proceedings of the National Academy of Sciences104(25): 10661–10666.10.1073/pnas.0610849104Search in Google Scholar

Mandat, T.S., Hurwitz, T. and Honey, C.R. (2006). Hypomania as an adverse effect of subthalamic nucleus stimulation: Report of two cases, Acta Neurochirurgica148(8): 895–898.10.1007/s00701-006-0795-4Search in Google Scholar

Mandat, T., Tykocki, T., Koziara, H., Koziorowski, D., Brodacki, B., Rola, R., Bonicki, W. and Nauman, P. (2011). Subthalamic deep brain stimulation for the treatment of Parkinson disease, Neurologia i Neurochirurgia Polska45(1): 32–36.10.1016/S0028-3843(14)60057-8Search in Google Scholar

Moran, A., Bar-Gad, I., Bergman, H. and Israel, Z. (2006). Real-time refinement of subthalamic nucleus targeting using Bayesian decision-making on the root mean square measure, Movement Disorders21(9): 1425–1431.10.1002/mds.2099516763982Search in Google Scholar

Nieuwenhuys, R., Voogd, J. and Van Huijzen, C. (2007). The Human Central Nervous System: A Synopsis and Atlas, Springer, Berlin.10.1007/978-3-540-34686-9Search in Google Scholar

Novak, P., Daniluk, S., Ellias, S.A. and Nazzaro, J.M. (2007). Detection of the subthalamic nucleus in microelectrographic recordings in Parkinson disease using the high-frequency (> 500 Hz) neuronal background, Journal of Neurosurgery106(1): 175–179.10.3171/jns.2007.106.1.17517236505Search in Google Scholar

Parent, A. and Hazrati, L.-N. (1995). Functional anatomy of the basal ganglia. II: The place of subthalamic nucleus and external pallidium in basal ganglia circuitry, Brain Research Reviews20(1): 128–154.Search in Google Scholar

Saleh, S., Swanson, K.I., Lake, W.B. and Sillay, K.A. (2015). Awake neurophysiologically guided versus asleep MRI-guided STN DBS for Parkinson disease: A comparison of outcomes using levodopa equivalents, Stereotactic and Functional Surgeny93(6): 419–426.10.1159/00044242526784455Search in Google Scholar

Schaltenbrand, G. (1977). Atlas for Stereotaxy of the Human Brain, Georg Thieme, Stuttgart.Search in Google Scholar

Schiaffino, L., Muñoz, A.R., Martínez, J.G., Villora, J.F., Gutiérrez, A. and Torres, I.M. (2016). STN area detection using K-NN classifiers for MER recordings in Parkinson patients during neurostimulator implant surgery, Journal of Physics: Conference Series705(1): 012050.10.1088/1742-6596/705/1/012050Search in Google Scholar

Shamir, R.R., Zaidel, A., Joskowicz, L., Bergman, H. and Israel, Z. (2012). Microelectrode recording duration and spatial density constraints for automatic targeting of the subthalamic nucleus, Stereotactic and Functional Neuro-surgery90(5): 325–334.10.1159/00033825222854414Search in Google Scholar

Smith, S.W. (1997). The Scientist & Engineer’s Guide to California Technical, Digital Signal Processing, Publishing, San Diego, CA.Search in Google Scholar

Temel, Y., Blokland, A., Steinbusch, H.W.M. and Visser-Vandewalle, V. (2005). The functional role of the subthalamic nucleus in cognitive and limbic circuits, Progress in Neurobiology76(6): 393–413.10.1016/j.pneurobio.2005.09.00516249050Search in Google Scholar

Valsky, D., Marmor-Levin, O., Deffains, M., Eitan, R., Blackwell, K. T., Bergman, H. and Israel, Z. (2017). Stop! border ahead: Automatic detection of subthalamic exit during deep brain stimulation surgery, Movement Disorders32(1): 70–79.10.1002/mds.26806547892727709666Search in Google Scholar

Williams, C.K.I. (2003). Learning with kernels: Support vector machines, regularization, optimization, and beyond, Journal of the American Statistical Association98(462): 489–489.10.1198/jasa.2003.s269Search in Google Scholar

Zaidel, A., Spivak, A., Shpigelman, L., Bergman, H. and Israel, Z. (2009). Delimiting subterritories of the human subthalamic nucleus by means of microelectrode recordings and a hidden Markov model, Movement Disorders24(12): 1785–1793.10.1002/mds.2267419533755Search in Google Scholar

eISSN:
2083-8492
Język:
Angielski
Częstotliwość wydawania:
4 razy w roku
Dziedziny czasopisma:
Mathematics, Applied Mathematics