I consider myself as a data science generalist, passionate about uncovering patterns through signal processing and machine learning. Most of my work involves Python for data processing, transformation, and machine learning. I also spend time developing APIs. I enjoy turning complex data into useful insights.

Research interest

natural language processing, biomedical signal processing, machine learning, fetal heart rate analysis

Selected Publications

	P. Abry, J. Spilka, R. Leonarduzzi, V. Chudáček, N. Pustelnik, M. Doret Sparse learning for Intrapartum fetal heart rate analysis In Biomedical Physics Engineering Express 4(3) 034002, 2018. web | .pdf | .bib | paper results
	J. Spilka, J. Frecon, R. Leonarduzzi, N. Pustelnik, P. Abry, M. Doret Sparse Support Vector Machine for Intrapartum Fetal Heart Rate Classification In IEEE Journal of Biomedical and Health Informatics, 21(3), 664 - 671, 2017. web | .pdf | .bib
	M. Doret, J. Spilka, V. Chudáček, P. Goncalves, P. Abry Fractal Analysis and Hurst Parameter for Intrapartum Fetal Heart Rate Variability Analysis: A Versatile Alternative to Frequency Bands and LF/HF Ratio In PLoS ONE, vol. 10, no. 8, p. e0136661, 08 2015. web | .pdf | .bib
	J. Spilka, J. Frecon, R. Leonarduzzi, N. Pustelnik, P. Abry, M. Doret Intrapartum Fetal Heart Rate Classification from Trajectory in Sparse SVM feature space In Ann Int Conf IEEE Eng Med Biol Soc (EMBC), Milan, Italy, August 2015, pp. 2335--2338. web | .pdf | .bib
	L. Hruban, J. Spilka, V. Chudáček, P. Janků, et al. Agreement on intrapartum cardiotocogram recordings between expert obstetricians In Journal of Evaluation in Clinical Practice, 21(4): 694-702, 2015. web | .pdf | .bib
	P. Karvelis, J. Spilka, G. Georgoulas, V. Chudáček, C. Stylios, L. Lhotská Combining Latent Class Analysis Labeling with Multiclass Approach for Fetal Heart Rate Categorization In Physiological Measurement 36, 1001-1024, 2015. web | .pdf | .bib
	J. Spilka, S.G. Roux, N.B. Garnier, P. Abry, P. Goncalves, and M. Doret Nearest-neighbor based wavelet entropy rate measures for intrapartum fetal heart rate variability In Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, 2813–2816, IEEE, 2014. web | .pdf | .bib
	J. Spilka, V. Chudáček, P. Janků, L. Hruban, M. Burša, M. Huptych, L. Zach, L. Lhotská. Analysis of obstetricians’ decision making on CTG recordings. Journal of Biomedical Informatics 2014, 51:72-79, 2014 web | .pdf | .bib
	V. Chudáček, J. Spilka, M. Burša, P. Janků, L. Hruban, M. Huptych, L. Lhotská. Open access intrapartum CTG database. BMC Pregnancy and Childbirth 2014 14(1):16, 2014. web | .pdf | .bib
	J. Spilka, V. Chudáček, M. Koucký, L. Lhotská, M. Huptych, P. Janků, G. Georgoulas, C. Stylios. Using nonlinear features for fetal heart rate classification. Biomedical Signal Processing and Control 7(4):350–357, 2012. web | .pdf | .bib
	V. Chudáček, J. Spilka, P. Janků, M. Koucký, L. Lhotská, and M. Huptych. Automatic evaluation of intrapartum fetal heart rate recordings: A comprehensive analysis of useful features. Physiological Measurement 32:1347–1360, 2011. web | .pdf | .bib
	J. Spilka, V. Chudáček, V. Kužílek, L. Lhotská, and M. Hanuliak. Detection of Inferior Myocardial Infarction: A Comparison of Various Decision Systems and Learning Algorithms. In Computers in Cardiology volume 37, 2010 web | .pdf | .bib