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david-guijo-rubio
Guijo-Rubio, David
Personal Information
Position:
Investigador postdoctoral Juan de la Cierva
Research areas:
Applications - Donor-recipient matching in liver transplants
Applications - Engine noise prediction
Applications - Weather forecasting
Applications - Health
Methodology - Machine learning
Methodology - Ordinal classification
Methodology - Time series
Location:
Campus de Rabanales, edificio Albert Einstein, 3ª Planta, Ala Sur, CP: 14014
Publications
ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target
A Hands-on Introduction to Time Series Classification and Regression
EBANO: A novel Ensemble BAsed on uNimodal Ordinal classifiers for the prediction of significant wave height
OS-024 The gender-equity model for liver allocation built on artificial intelligence (GEMA-AI) improves outcome predictions among liver transplant candidates
Energy Flux Prediction Using an Ordinal Soft Labelling Strategy
Medium- and Long-Term Wind Speed Prediction Using the Multi-task Learning Paradigm
Data Augmentation Techniques for Extreme Wind Prediction Improvement
O-Hydra: A Hybrid Convolutional and Dictionary-Based Approach to Time Series Ordinal Classification
Age Estimation Using Soft Labelling Ordinal Classification Approaches
Unsupervised feature based algorithms for time series extrinsic regression
Cluster analysis and forecasting of viruses incidence growth curves: Application to SARS-CoV-2
Development and validation of the Gender-Equity Model for Liver Allocation (GEMA) to prioritise candidates for liver transplantation: a cohort study
Machine Learning Applications in Real-World Time Series Problems
Barycentre Averaging for the Move-Split-Merge Time Series Distance Measure
Clustering Time Series with k-Medoids Based Algorithms
Performance of the gender-equity model for liver allocation (GEMA-Na) within the first 30 and 60 days of listing
UTILIDAD DEL GENDER-EQUITY MODEL FOR LIVER ALLOCATION (GEMA) EN UN CONTEXTO DE ACORTAMIENTO DE LA LISTA DE ESPERA DE TRASPLANTE HEPÁTICO
A Dictionary-Based Approach to Time Series Ordinal Classification
Ordinal classification approach for donor-recipient matching in liver transplantation with circulatory death donors
Gramian Angular and Markov Transition Fields applied to Time Series Ordinal Classification
One month in advance prediction of air temperature from Reanalysis data with Explainable Artificial Intelligence techniques
Emparejamiento donante-receptor durante la donación en asistolia controlada con perfusión regional normotérmica: papel de los clasificadores de machine learning como modelos predictivos de la supervivencia del injerto
Corrección de la disparidad de género en el acceso al trasplante hepático
Generalised Triangular Distributions for ordinal deep learning: novel proposal and optimisation
An Evolutionary Artificial Neural Network approach for spatio-temporal wave height time series reconstruction
Assessing the Efficient Market Hypothesis for Cryptocurrencies with High-Frequency Data using Time Series Classification
Development and validation of the gender-equity model for liver allocation (GEMA) to prioritize liver transplant candidates
COVID-19 contagion forecasting framework based on curve decomposition and evolutionary artificial neural networks: A case study in Andalusia, Spain
Clustering of COVID-19 Time Series Incidence Intensity in Andalusia, Spain
Simultaneous short-term significant wave height and energy flux prediction using zonal multi-task evolutionary artificial neural networks
Hackathon en docencia: aprendizaje automático aplicado a Ciencias de la Vida
Hackathon in teaching: applying machine learning to Life Sciences tasks
Gamifying the classroom for the acquisition of skills associated with Machine Learning: a two-year case study
Time series clustering based on the characterisation of segment typologies
Potenciando el perfil profesional Científico de Datos mediante dinámicas de competición
Clustering, prediction and ordinal classification of time series using machine learning techniques: applications
Studying the effect of different Lp norms in the context of Time Series Ordinal Classification
ReLU-based activations: analysis and experimental study for deep learning
Enhancing the ORCA framework with a new Fuzzy Rule Base System implementation compatible with the JFML library
Statistical methods versus machine learning techniques for donor-recipient matching in liver transplantation
Evolutionary artificial neural networks for accurate solar radiation prediction
Machine learning methods in organ transplantation
Ordinal regression algorithms for the analysis of convective situations over Madrid-Barajas airport
Validation of artificial neural networks to model the acoustic behaviour of induction motors
Prediction of convective clouds formation using evolutionary neural computation techniques
Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals
Short- and long-term energy flux prediction using Multi-Task Evolutionary Artificial Neural Networks
Ordinal versus nominal time series classification
Time series ordinal classification via shapelets
Predicción de altura de ola mediante discretización basada en distribuciones utilizando clasificación ordinal
Validation of multitask artificial neural networks to model desiccant wheels activated at low temperature
Modelling survival by machine learning methods in liver transplantation: application to the UNOS dataset
A hybrid approach to time series classification with shapelets
Time series clustering based on the characterisation of segment typologies
Distribution-Based Discretisation and Ordinal Classification Applied to Wave Height Prediction
Algoritmos de aprendizaje automático para predicción de niveles de niebla usando ventanas estáticas y dinámicas
Prediction of low-visibility events due to fog using ordinal classification
Hybrid Weighted Barebones Exploiting Particle Swarm Optimization Algorithm for Time Series Representation
A coral reef optimization algorithm for wave height time series segmentation problems
Clustering de Series Temporales basado en la Extracción de Tipologías de Segmentos
Multiclass Prediction of Wind Power Ramp Events Combining Reservoir Computing and Support Vector Machines
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Projects
Clasificación ordinal basada en aprendizaje profundo y neuro-evolución (ORCA-DEEP)
Modelo de emparejamiento donante-receptor en trasplante hepático mediante Inteligencia Artificial con donantes en asistolia
Métodos de Aprendizaje Profundo en clasificación ORDINAL (MAP-ORDINAL)
Aprendizaje dinámico de modelos de curvas de infectados y de número de camas hospitalarias y camas UCI ocupadas por COVID-19 en Andalucía mediante técnicas estadísticas y de Inteligencia Artificial
Modelos de Aprendizaje de Máquina para la determinación óptima de la Supervivencia y la Asignación Donante/REceptor en trasplante hepático. MASS-ALLOCATION
Uso de inteligencia artificial para eliminar disparidades de género en el acceso al trasplante hepático: “Gender-equality MELD”
HETICA: Una HErramienta TIC para la organización de tareas escolares en personas con síndrome de Asperger
Algoritmos de clasificación ordinal en energias renovables (ORdinal Classification and prediction Algorithms in Renewable Energy, ORCA-RE)
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