Cristina Rubio Escudero

@article{prisma258560,

title = {Online forecasting using neighbor-based incremental learning for electricity markets},

author = {L. Melgar-García and D. Gutiérrez-Avilés and C. Rubio-Escudero and A. Troncoso},

url = {https://prisma.us.es/publicacion/258560},

doi = {10.1007/s00521-024-10876-x},

year  = {2025},

date = {2025-01-01},

journal = {NEURAL COMPUTING & APPLICATIONS},

volume = {37},

number = {27},

pages = {22923–22940},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{prisma243647,

title = {A comparison of time series lags and non-lags in Spanish electricity price forecasting using data science models},

author = {B Vega-Márquez and J Solís-García and IA Nepomuceno-Chamorro and C Rubio-Escudero},

url = {https://prisma.us.es/publicacion/243647},

doi = {10.1093/jigpal/jzae034},

year  = {2024},

date = {2024-01-01},

journal = {Logic Journal of the IGPL},

volume = {32},

number = {6},

pages = {1036–1047},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{prisma231980,

title = {Emerging trends in big data analytics and natural disasters},

author = {Francisco Martínez-Álvarez and Rudolf Scitovski and Cristina Rubio-Escudero and Antonio Morales-Esteban},

url = {https://prisma.us.es/publicacion/231980},

doi = {10.1016/j.cageo.2023.105465},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {COMPUTERS & GEOSCIENCES},

journal = {COMPUTERS & GEOSCIENCES},

volume = {182},

note = {Tipo en PRISMA: Editorial.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articleh,

title = {A Novel Distributed Forecasting Method Based on Information Fusion and Incremental Learning for Streaming Time Series},

author = {Laura Melgar-García and David Gutiérrez-Avilés and Cristina Rubio-Escudero and Alicia Troncoso},

doi = {10.2139/ssrn.4326600},

year  = {2023},

date = {2023-01-01},

journal = {SSRN Electronic Journal},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1016/j.engappai.2023.106326,

title = {Identifying novelties and anomalies for incremental learning in streaming time series forecasting},

author = {Laura Melgar-García and David Gutiérrez-Avilés and Cristina Rubio-Escudero and Alicia Troncoso},

url = {https://doi.org/10.1016/j.engappai.2023.106326},

doi = {10.1016/j.engappai.2023.106326},

year  = {2023},

date = {2023-01-01},

journal = {Engineering Applications of Artificial Intelligence},

volume = {123},

pages = {106326},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{prisma226429,

title = {PDSS: A pharmacological decision support system for diabetics patients with COVID-19},

author = {Isabel Amaya-Rodríguez and Nekane Larburu and María Rollán Martinez-Herrera and Kristin Rebescher and Iván Macia and Miguel Á. Armengol de la Hoz and Cristina Rubio-Escudero and Alba Garín-Muga},

url = {https://prisma.us.es/publicacion/226429},

doi = {10.3233/SHTI230197},

year  = {2023},

date = {2023-01-01},

journal = {Studies in Health Technology and Informatics},

volume = {302},

pages = {521–525},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{app12083987,

title = {MOMIC: A Multi-Omics Pipeline for Data Analysis, Integration and Interpretation},

author = {Laura Madrid-Márquez and Cristina Rubio-Escudero and Beatriz Pontes and Antonio González-Pérez and José C. Riquelme and Maria E. Sáez},

url = {https://www.mdpi.com/2076-3417/12/8/3987},

doi = {10.3390/app12083987},

issn = {2076-3417},

year  = {2022},

date = {2022-01-01},

journal = {Applied Sciences},

volume = {12},

number = {8},

abstract = {Background and Objectives: The burst of high-throughput omics technologies has given rise to a new era in systems biology, offering an unprecedented scenario for deriving meaningful biological knowledge through the integration of different layers of information. Methods: We have developed a new software tool, MOMIC, that guides the user through the application of different analysis on a wide range of omic data, from the independent single-omics analysis to the combination of heterogeneous data at different molecular levels. Results: The proposed pipeline is developed as a collection of Jupyter notebooks, easily editable, reproducible and well documented. It can be modified to accommodate new analysis workflows and data types. It is accessible via momic.us.es, and as a docker project available at github that can be locally installed. Conclusions: MOMIC offers a complete analysis environment for analysing and integrating multi-omics data in a single, easy-to-use platform.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articlei,

title = {Sa1267: INTRODUCING JOINT MODELING TECHNIQUES FOR PERSONALIZED PREDICTIONS IN CELIAC DISEASE},

author = {Lidia Serrano and Alfonso Rodríguez-Herrera and Carles Serrat and Cristina Rubio-Escudero},

doi = {10.1016/S0016-5085(22)60867-9},

year  = {2022},

date = {2022-01-01},

journal = {Gastroenterology},

volume = {162},

pages = {S-361},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articlej,

title = {A new big data triclustering approach for extracting three-dimensional patterns in precision agriculture},

author = {Laura Melgar-García and David Gutiérrez-Avilés and Maria Teresa Godinho and Rita Espada and Isabel Brito and Francisco Martínez-Álvarez and Alicia Troncoso and Cristina Rubio-Escudero},

doi = {10.1016/j.neucom.2021.06.101},

year  = {2022},

date = {2022-01-01},

journal = {Neurocomputing},

volume = {500},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articlek,

title = {MOMIC: A Multi-Omics Pipeline for Data Analysis, Integration and Interpretation},

author = {Laura Madrid-Márquez and Cristina Rubio-Escudero and Beatriz Pontes and Antonio González-Pérez and José Riquelme and Maria Saez},

doi = {10.3390/app12083987},

year  = {2022},

date = {2022-01-01},

journal = {Applied Sciences},

volume = {12},

pages = {3987},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articlec,

title = {OCEAn: Ordinal Classification with an Ensemble Approach},

author = {Belén Vega and Isabel Nepomuceno-Chamorro and Cristina Rubio-Escudero and José Riquelme},

doi = {10.1016/j.ins.2021.08.081},

year  = {2021},

date = {2021-01-01},

journal = {Information Sciences},

volume = {580},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articled,

title = {Use of Deep Learning Architectures for Day-Ahead Electricity Price Forecasting over Different Time Periods in the Spanish Electricity Market},

author = {Belén Vega and Cristina Rubio-Escudero and Isabel Nepomuceno-Chamorro and Angel Arcos-Vargas},

doi = {10.3390/app11136097},

year  = {2021},

date = {2021-01-01},

journal = {Applied Sciences},

volume = {11},

pages = {6097},

keywords = {},

pubstate = {published},

tppubtype = {article}

}