Publicaciones
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One-Week Suicide Risk Prediction Using Real-Time Smartphone Monitoring: Prospective Cohort Study
Barrigon, M. L., Romero-Medrano, L., Moreno-Muñoz, P., Porras-Segovia, A., Lopez-Castroman, J., Courtet, P., Artés-Rodríguez, A. & Baca-Garcia, E. (2023).
J. Méd. Internet Res. 25, e43719. https://doi.org/10.2196/43719
Automatic patient functionality assessment from multimodal data using deep learning techniques – Development and feasibility evaluation
Sükei, E., Leon-Martinez, S. de, Olmos, P. M. & Artés, A. (2023).
Internet Interv. 100657 (2023). https://doi.org/10.1016/j.invent.2023.100657
Multi-Source Change-Point Detection over Local Observation Models
Romero-Medrano, L. & Artés-Rodríguez, A. (2022).
Pattern Recogn 109116. https://doi.org/10.1016/j.patcog.2022.109116
Medical Data Wrangling With Sequential Variational Autoencoders
Barrejón, D., Olmos, P. M., & Artés-Rodríguez, A. (2022).
IEEE Journal of Biomedical and Health Informatics, 26(6), 2737–2745. https://doi.org/10.1109/jbhi.2021.3123839
Real-world feasibility and acceptability of real-time suicide risk monitoring via smartphones: A 6-month follow-up cohort
Porras-Segovia, A., Díaz-Oliván, I., Barrigón, M. L., Moreno, M., Artés-Rodríguez, A., Pérez-Rodríguez, M. M., & Baca-García, E. (2022).
Journal of Psychiatric Research. https://doi.org/10.1016/j.jpsychires.2022.02.026
Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning–Based Ecological Momentary Assessment Study
Ryu, J., Sükei, E., Norbury, A., Liu, S.H, Campaña-Montes, J.J., Baca-Garcia, E., Artés, A., Perez-Rodriguez, M.M. (2021).
JMIR Mental Health. https://doi.org/10.2196/30833
Use of Ecological Momentary Assessment Through a Passive Smartphone-Based App (eB2) by Patients With Schizophrenia: Acceptability Study
Lopez-Morinigo, J.-D., Barrigón, M. L., Porras-Segovia, A., Ruiz-Ruano, V. G., Martínez, A. S. E., Escobedo-Aedo, P. J., Alonso, S. S., Iturralde, L. M., Lorenzo, L. M., Artés-Rodríguez, A., David, A. S., & Baca-García, E. (2021).
Journal of Medical Internet Research, 23(7), e26548. https://doi.org/10.2196/26548
Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach
Sükei, E., Norbury, A., Perez-Rodriguez, M. M., Olmos, P. M., Artés, A. (2021).
JMIR Mhealth Uhealth. https://doi.org/10.2196/24465
Use of Ecological Momentary Assessment Through a Passive Smartphone-Based App (eB2) by Patients With Schizophrenia: Acceptability Study
Lopez-Morinigo, J.-D., Barrigón, M. L., Porras-Segovia, A., Ruiz-Ruano, V. G., Martínez, A. S. E., Escobedo-Aedo, P. J., Alonso, S. S., Iturralde, L. M., Lorenzo, L. M., Artés-Rodríguez, A., David, A. S., & Baca-García, E. (2021).
Journal of Medical Internet Research, 23(7), e26548. https://doi.org/10.2196/26548
Social media and smartphone app use predicts maintenance of physical activity during Covid-19 enforced isolation in psychiatric outpatients
Norbury, A., Liu, S.H., Campaña-Montes, J.J., Romero-Medrano, L., Barrigón, M.L., Smith, E., Artés, A., Baca-García, E., Pérez-Rodríguez, M.M. (2020).
Mol Psychiatry. https://doi.org/10.1038/s41380-020-00963-5
Ecological Momentary Assessment for Monitoring Risk of Suicide Behavior
Carretero, P., Campaña-Montes, J., Artés-Rodríguez, A.
Smartphone-based ecological momentary assessment (EMA) in psychiatric patients and student controls: A real-world feasibility study
Porras-Segovia, A., Molina-Madueño, R., Berrouiguet, S., López-Castroman, J., Barrigón, M., Pérez-Rodríguez, M., Marco, J., Díaz-Oliván, I., León, S., Courtet, P., Artés-Rodríguez, A., Baca-García, E. (2020).
Journal of Affective Disorders. https://dx.doi.org/10.1016/j.jad.2020.05.067
Multinomial Sampling for Hierarchical Change-Point Detection
Romero-Medrano, L., Moreno-Muñoz, P., Artés-Rodríguez, A. (2020).
2020 IEEE 30th International Workshop on Machine Learning for Signal Processing (MLSP) 00(), 1-6. https://dx.doi.org/10.1109/mlsp49062.2020.9231616
Study protocol of a randomised clinical trial testing whether metacognitive training can improve insight and clinical outcomes in schizophrenia
Lopez-Morinigo, J., Ruiz-Ruano, V., Martínez, A., Estévez, M., Mata-Iturralde, L., Muñoz-Lorenzo, L., Sánchez-Alonso, S., Artés-Rodríguez, A., David, A., Baca-García, E. (2020).
BMC Psychiatry 20(1), 30. https://dx.doi.org/10.1186/s12888-020-2431-x
Continual Learning for Infinite Hierarchical Change-Point Detection
Moreno-Muñoz, P., Ramírez, D., Artés-Rodríguez, A. (2019).
Assessment of e-Social Activity in Psychiatric Patients
Bonilla-Escribano, P., Ramirez, D., Sedano-Capdevila, A., Campana-Montes, J., Baca-Garcia, E., Courtet, P., Artes-Rodriguez, A. (2019).
IEEE Journal of Biomedical and Health Informatics 23(6), 1-1. https://dx.doi.org/10.1109/jbhi.2019.2918687
Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol
Berrouiguet, S., Barrigón, M., Castroman, J., Courtet, P., Artés-Rodríguez, A., Baca-Garcia, E. (2019).
BMC Psychiatry 19(1), 570. https://dx.doi.org/10.1186/s12888-019-2260-y
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
Berrouiguet, S., Ramírez, D., Barrigón, M., Moreno-Muñoz, P., Camacho, R., Baca-Garcia, E., Artés-Rodríguez, A. (2018).
JMIR mHealth and uHealth 6(12), e197. https://dx.doi.org/10.2196/mhealth.9472
Machine learning and data mining: strategies for hypothesis generation
Oquendo, M., Baca-Garcia, E., Artés-Rodríguez, A., Pérez-Cruz, F., Galfalvy, H., Blasco-Fontecilla, H., Madigan, D., Duan, N. (2012).
Molecular Psychiatry 17(10), 956 – 959. https://dx.doi.org/10.1038/mp.2011.173
