Artículos

  • Sastre-Buades, A., Alacreu-Crespo, A., Courtet, P., Baca-García, E. and Barrigón, M. L. (2021). Decision-making in suicidal behavior: A systematic review and meta-analysis. Neuroscience and Biobehavioral Reviews, 131, 642-662. Open access https://doi.org/10.1016/j.neubiorev.2021.10.005
  • Moreno-Pino, F., Porras-Segovia, A., López Esteban, P., Artés-Rodríguez, A. and Baca-García, E. (2019). Validation of Fitbit Charge 2 and Fitbit Alta HR Against Polysomnography for Assessing Sleep in Adults with Obstructive Sleep Apnea. Journal of Clinical Sleep Medicine, 15(11), 1645-1653. Open access https://doi.org/10.5664/jcsm.8032
  • Garg, V., Santamaria, I., Ramírez, D. and Scharf, L. L. (2019). Subspace Averaging and Order Determination for Source Enumeration. IEEE Transactions on signal Processing, 67(11), 3028-3041. Open access https://doi.org/10.1109/TSP.2019.2912151
  • Barrigon, M.L., Courtet, P., Oquendo, M. and Baca-García, E. (2019). Precision Medicine and Suicide: an Opportunity for Digital Health. Curr. Psychiatry Rep., 21, 131. Open access https://doi.org/10.1007/s11920-019-1119-8
  • Luengo, D., Ríos-Muñoz, G., Elvira, V., Sánchez, C. and Artés-Rodríguez, A. (2019). Hierarchical algorithms for causality retrieval in atrial fibrillation intracavitary electrograms. IEEE Journal of Biomedical and Health Informatics, 23(1), 143-155. Open access https://doi.org/10.1109/JBHI.2018.2805773
  • Peis, I., Olmos, P. M., Vera-Varela, C., Barrigón, M. L., Courtet, P., Baca-García, E., Artés-Rodríguez, A. 2019. Deep Sequential Models for Suicidal Ideation from Multiple Source Data. IEEE J. Biomed. Health Inform., 23(6), 2286-2293. Open Access https://doi.org/10.1109/JBHI.2019.2919270
  • Berrouiguet, S., Barrigón, M.L., Castroman, Courtet, P., Artés-Rodríguez, A. and Baca-García, E. (2019). Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol. BMC Psychriaty, 19(1), 277. Open access https://doi.org/10.1186/s12888-019-2260-y
  • Pradier, M.F., Reis, B., Jukofsky, L., Milleti, F., Ohtomo, T., Pérez-Cruz, F. and Puig, O. (2019). Case-control Indian buffet process identifies biomarkers of response to Codrituzumab. BMC Cancer, 19, 278. Open access https://doi.org/10.1186/s12885-019-5472-0
  • Koblents, E., Mariño, I.P. and Míguez, J. (2019). Bayesian Computation Methods for Inference in Stochastic Kinetic Models. Complexity, 2019. Open access https://doi.org/10.1155/2019/7160934
  • Bonilla-Escribano, P., Ramírez, D., Sedano-Capdevila, A., Campaña-Montes, J. J., Baca-García, E., Courtet, P., Artés-Rodríguez, A. (2019). Assessment of e-Social Activity in Psychiatric Patients. IIEEE J. Biomed. Health Inform., 23(6), 2247-2256. Open Access https://doi.org/10.1109/JBHI.2019.2918687
  • Akyildiz, Ö. D., Chouzenoux, É., Elvira, V. and Míguez, J. (2019). A Probabilistic Incremental Proximal Gradient Method. IEEE Signal Processing Letters, 26(8), 1257-1261. Open access https://doi.org/10.1109/LSP.2019.2926926
  • Ramírez, D., Romero, D., Vía, J., López-Valcarce, R. and Santamaría, I. (2018). Testing Equality of Multiple Power Spectral Density Matrices. IEEE Transactions on Signal Processing, 66(23), 6268-6280. Open access https://doi.org/10.1109/TSP.2018.2875884
  • Pérez-Vieites, S., Mariño, I. P. and Míguez, J. (2018). Probabilistic scheme for joint parameter estimation and state prediction in complex dynamical systems. Physical Review E., 98, 063305. Open access https://doi.org/10.1103/PhysRevE.98.063305
  • Crisan, D., Míguez, J. and Ríos-Muñoz, G. R. (2018). On the performance of parallelisation schemes for particle filtering. Eurasip Journal on Advances in Signal Processing, 2018, 31. https://doi.org/10.1186/s13634-018-0552-x
  • Lacasa, L., Mariño, I. P., Míguez, J., Nicosia, V., Roldán, É., Lisica, A., Grill, S. W. and Gómez-Gardeñes, J. (2018). Multiplex Decomposition of Non-Markovian Dynamics and the Hidden Layer Reconstruction Problem. Phys. Rev. X, 8, 031038. Open access https://doi.org/10.1103/PhysRevX.8.031038
  • Pries, A., Ramírez, D. and Schreier, P.J. (2018). LMPIT-Inspired Tests for Detecting a Cyclostationary Signal in Noise with Spatio-Temporal Structure. IEEE Transactions on Wireless Communications, 17(9), 6321-6334. Open access https://doi.org/10.1109/TWC.2018.2859314
  • Horstmann, S., Ramírez, D., Schreier, P.J. (2018). Joint Detection of Almost-Cyclostationary Signals and Estimation of Their Cycle Period. IEEE Signal Processing Letters, 25(11), 1695-1699. Open access https://doi.org/10.1109/LSP.2018.2871961
  • Hernando-Gallego, F., Luengo, D., Artés-Rodríguez, A. (2018). Feature Extraction of Galvanic Skin Responses by Nonnegative Sparse Deconvolution. IEEE Journal of Biomedical and Health Informatics, 22(5), 1385-1394. Open access https://doi.org/10.1109/JBHI.2017.2780252
  • Utkovski, Z., Pradier, M. F., Stojkoski, V., Pérez-Cruz, F. and Kocarev L. (2018). Economic Complexity Unfolded: An Interpretable Model for the Productive Structure of Economies” PLoS ONE, 13(8). Open access https://doi.org/10.1371/journal.pone.0200822
  • Ríos-Muñoz, A., Árenal, Á., Artés-Rodríguez, A. (2018). Corrigendum: Real-time rotational activity detection in atrial fibrillation. Frontiers in Physiology, 9, 1260. Open access https://doi.org/10.3389/fphys.2018.01260
  • Berrouiguet, S., Ramírez, D., Barrigón, M.L., Moreno-Muñoz, P., Carmona Camacho, R., Baca-García, E. and Artés-Rodríguez, A. (2018). Combining continuous smartphone native sensors data capture and unsupervised data mining techniques for behavioral changes detection: A case series of the evidence-based behavior (eB2) study. JMIR mHealth and uHealth, 6(12). Open access https://doi.org/10.2196/mhealth.9472
  • Míguez, J., Mariño, I. P. and Vázquez, M. A. (2018). Analysis of a nonlinear importance sampling scheme for Bayesian parameter estimation in state-space models. Signal Processing, 142, 281-291. Open access https://doi.org/10.1016/j.sigpro.2017.07.030
  • Vázquez, M. A., Mariño, I.P., Blyuss, O., Ryan, A., Gentry-Maharaj, A., Kalsi, J., Manchanda, R., Jacobs, I., Menon, U. and Zaikin, A. (2018). A quantitative performance study of two automatic methods for the diagnosis of ovarian cancer. Biomedical Signal Processing and Control, 46, 86-93. Open access https://doi.org/10.1016/j.bspc.2018.07.001
  • Ríos-Muñoz, A., Árenal, Á., Artés-Rodríguez, A. (2018). Real-time Rotational Activity Detection in Atrial Fibrillation. Frontiers in Physiology, 9, 1260. Open access https://doi.org/10.3389/fphys.2018.00208
  • Crisan, D. and Míguez, J. (2018). Nested particle filters for online parameter estimation in discrete-time state-space Markov models. Bernoulli, 24(4A), 3039-3086. Open access https://doi.org/10.3150/17-BEJ954
  • Mariño, I. P., Blyuss, O., Ryan, A., Gentry-Maharaj, A., Timms, J. F., Dawnay, A., Kalsi, J., Jacobs, I., Menon, U. and Zaikin, A. (2017). Change-point of multiple biomarkers in women with ovarian cancer. Biomedical Signal Processing Control, 33, 169-177. Open access https://doi.org/10.1016/j.bspc.2016.11.015
  • Crisan, D., and Míguez, J. (2017). Uniform convergence over time of a nested particle filtering scheme for recursive parameter estimation in state-space Markov models. Advances in Applied Probability, 49(4), 1170-1200. Open access https://doi.org/10.1017/apr.2017.38
  • Mariño, I. P., Zaikin, A. and Míguez, J. (2017). A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks. PLoS ONE, 12(8). Open access https://doi.org/10.1371/journal.pone.0182015
  • Bugallo, M. F., Elvira, V., Martino, L., Luengo, D., Míguez, J. and Djuric, P.M. (2017). Adaptive Importance Sampling: The past, the present, and the future. IEEE Signal Processing Magazine, 34(4), 60-79. Open access https://doi.org/10.1109/MSP.2017.2699226
  • Boloix-Tortosa, R., Murillo-Fuentes, J.J., Santos, I. and Pérez-Cruz, F. (2017). Widely Linear Complex-Valued Kernel Methods for Regression. IEEE Transactions on Signal Processing, 65(19), 5240-5248. Open access https://doi.org/10.1109/TSP.2017.2726991
  • Elvira, V., Míguez, J. and Djuric, P.M. (2017). Adapting the Number of Particles in Sequential Monte Carlo Methods Through an Online Scheme for Convergence Assessment. IEEE Transactions on Signal Processing, 65(7), 1781-1794. Open access https://doi.org/10.1109/TSP.2016.2637324
  • Barrigón, M.L., Berrouiguet, S., Carballo, J. J., Bonal-Giménez, C., Fernández-Navarro, P., Pfang, B., Delgado-Gómez, D., Courtet, P., Aroca, F., López-Castroman, J., Artés-Rodríguez, A., Baca-García, E. and MEmind study group. (2017). User profiles of an electronic mental health tool for ecological momentary assessment: MEmind. International Journal of Methods in Psychiatric Research, 26(1), e1554. Open access https://doi.org/10.1002/mpr.1554
  • Pradier, M. F., Olmos, P. M. and Pérez-Cruz, F. (2016). Entropy-Constrained Scalar Quantization with a Lossy-Compressed Bit. Entropy, 18(12), 449. Open access https://doi.org/10.3390/e18120449
  • Song, Y., Schreier, P. J., Ramírez, D. and Hasija, T. (2016). Canonical correlation analysis of high-dimensional data with very small sample support. Signal Processing, 128, 449–458. Open access https://doi.org/10.1016/j.sigpro.2016.05.020
  • Valera, I., Ruiz, F. J. R. and Pérez-Cruz, F. (2016). Infinite Factorial Unbounded-State Hidden Markov Model. IEEE Trans. Pattern Anal. Mach. Intell., 38(9), 1816–1828. Open access https://doi.org/10.1109/TPAMI.2015.2498931
  • Nazábal, A., García-Moreno, P., Artés-Rodríguez, A. and Ghahramani, Z. (2016). Human Activity Recognition by Combining a Small Number of Classifiers. IEEE J. Biomed. Heal. informatics, 20(5), 1342–1351. Open access https://doi.org/10.1109/JBHI.2015.2458274
  • Valera, I., Ruiz, F. J. R., Olmos, P. M., Blanco, C. and Pérez-Cruz, F. (2016Infinite Continuous Feature Model for Psychiatric Comorbidity Analysis. Neural Comput., 28(2), 354–381. Open access https://doi.org/10.1162/NECO_a_00805