Publicaciones

Nuestra esencia es la innovación e investigación. Creemos firmemente en la mejora de la atención al paciente gracias a la tecnología e investigación en concreto en las áreas del comportamiento humano e inteligencia artificial aplicada a salud mental.​

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.

https://dx.doi.org/10.1007/7854_2020_170

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).

https://arxiv.org/abs/1910.10087

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

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