• M-Mode Ultrasound Examination of Soleus Muscle in Healthy Subjects: Intra- and Inter-Rater Reliability Study 

      Romero Morales, Carlos; Calvo-Lobo, César; Navarro Flores, Emmanuel; Mazoteras-Pardo, Victoria; García-Bermejo, Paula; Martínez-Jiménez, Eva María; De-la-Cruz-Torres, Blanca; López-López, Daniel (2020-12)
      [Abstract] Objective: M-mode ultrasound imaging (US) reflects the motion of connective tissue within muscles. The objectives of this study were to evaluate inter-rater and intra-rater reliability of soleus muscle measurements ...
    • M. Ferreiro et alii, A edición da Poesía Trobadoresca en Galiza 

      Eirín, Leticia (Universidade da Coruña, 2009)
    • M1 inhibition dependency on slowing of muscle relaxation after brief and fast fatiguing repetitive movements: preliminary results 

      Madinabeitia-Mancebo, Elena; Madrid, Antonio; Cudeiro, Javier; Arias, Pablo (Springer, 2018-10-16)
      [Abstract] This work presents preliminary results on the association between central and peripheral expressions of muscle fatigue induced by unresisted repetitive movements. We tested cortico-spinal excitability and ...
    • M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines 

      Elbadawi, Moe; Muñiz, Brais; Gavins, Francesca K.H.; Ong, Jun Jie; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (Elsevier B.V., 2020-11)
      [Abstract]: Artificial intelligence (AI) has the potential to reshape pharmaceutical formulation development through its ability to analyze and continuously monitor large datasets. Fused deposition modeling (FDM) ...
    • Machine Learning Algorithms Reveals Country-Specific Metagenomic Taxa from American Gut Project Data 

      Liñares Blanco, Jose; Fernández-Lozano, Carlos; Seoane Fernández, José Antonio; López-Campos, Guillermo (NLM (Medline), 2021)
      [Abstract] In recent years, microbiota has become an increasingly relevant factor for the understanding and potential treatment of diseases. In this work, based on the data reported by the largest study of microbioma in ...
    • Machine learning analysis of TCGA cancer data 

      Liñares Blanco, Jose; Pazos, A.; Fernández-Lozano, Carlos (PeerJ Inc., 2021)
      [Abstract] In recent years, machine learning (ML) researchers have changed their focus towards biological problems that are difficult to analyse with standard approaches. Large initiatives such as The Cancer Genome Atlas ...
    • Machine Learning Analysis of the Human Infant Gut Microbiome Identifies Influential Species in Type 1 Diabetes 

      Fernández-Edreira, Diego; Liñares Blanco, Jose; Fernández-Lozano, Carlos (Elsevier, 2021)
      [Abstract] Diabetes is a disease that is closely linked to genetics and epigenetics, yet mechanisms for clarifying the onset and/or progression of the disease have sometimes not been fully managed. In recent years and due ...
    • Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes 

      Liñares Blanco, Jose; Fernández-Lozano, Carlos; Seoane Fernández, José Antonio; López-Campos, Guillermo (FRONTIERS MEDIA S.A., 2022)
      [Abstract] Inflammatory bowel disease (IBD) is a chronic disease with unknown pathophysiological mechanisms. There is evidence of the role of microorganims in this disease development. Thanks to the open access to multiple ...
    • Machine Learning Based Moored Ship Movement Prediction 

      Alvarellos, Alberto; Figuero, A.; Carro Fidalgo, Humberto; Costas Gómez, Raquel; Sande, José; Guerra, Andrés; Peña González, Enrique; Rabuñal, Juan R. (MDPI, 2021)
      [Abstract] Several port authorities are involved in the R+D+i projects for developing port management decision-making tools. We recorded the movements of 46 ships in the Outer Port of Punta Langosteira (A Coruña, Spain) ...
    • Machine learning for multivariate time series with the R package mlmts 

      López-Oriona, Ángel; Vilar, José (Elsevier B.V., 2023-06)
      [Abstract]: Time series data are ubiquitous nowadays. Whereas most of the literature on the topic deals with univariate time series, multivariate time series have typically received much less attention. However, the ...
    • Machine Learning in Management of Precautionary Closures Caused by Lipophilic Biotoxins 

      Molares-Ulloa, Andrés; Fernández-Blanco, Enrique; Pazos, A.; Rivero, Daniel (Elsevier, 2022)
      [Abstract] Mussel farming is one of the most important aquaculture industries. The main risk to mussel farming is harmful algal blooms (HABs), which pose a risk to human consumption. In Galicia, the Spanish main producer ...
    • Machine learning predicts 3D printing performance of over 900 drug delivery systems 

      Muñiz, Brais; Elbadawi, Moe; Ong, Jun Jie; Pollard, Thomas; Song, Zhe; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (Elsevier B.V., 2021-09)
      [Abstract]: Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy ...
    • Machine Learning Techniques for Single Nucleotide Polymorphism—Disease Classification Models in Schizophrenia 

      Aguiar-Pulido, Vanessa; Seoane, José A.; Rabuñal, Juan R.; Dorado, Julián; Pazos, A.; Munteanu, Cristian-Robert (Molecular Diversity Preservation International, 2010)
      [Abstract] Single nucleotide polymorphisms (SNPs) can be used as inputs in disease computational studies such as pattern searching and classification models. Schizophrenia is an example of a complex disease with an important ...
    • Machine Learning Techniques to Predict Different Levels of Hospital Care of CoVid-19 

      Hernández-Pereira, Elena; Fontenla-Romero, Óscar; Bolón-Canedo, Verónica; Cancela, Brais; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo (Springer, 2022)
      [Abstract] In this study, we analyze the capability of several state of the art machine learning methods to predict whether patients diagnosed with CoVid-19 (CoronaVirus disease 2019) will need different levels of hospital ...
    • Machine Learning to Compute Implied Volatility from European/American Options Considering Dividend Yield 

      Liu, Shuaiqiang; Leitao, Álvaro; Borovykh, Anastasia; Oosterlee, Cornelis (MDPI AG, 2020-09-15)
      [Abstract] Computing implied volatility from observed option prices is a frequent and challenging task in finance, even more in the presence of dividends. In this work, we employ a data-driven machine learning approach ...
    • Machine Learning-Based Radon Monitoring System 

      Valcarce, Diego; Alvarellos, Alberto; Rabuñal, Juan R.; Dorado, Julián; Gestal, M. (MDPI, 2022)
      [Abstract] Radon (Rn) is a biological threat to cells due to its radioactivity. It is capable of penetrating the human body and damaging cellular DNA, causing mutations and interfering with cellular dynamics. Human exposure ...
    • Machine-learning predicted and actual 2-year structural progression in the IMI-APPROACH cohort 

      Jansen, Mylène P.; Wirth, Wolfgang; Bacardit, Jaume; van Helvoort, Eefje M.; Marijnissen, Anne C.A.; Kloppenburg, Margreet; Blanco García, Francico J; Haugen, Ida K.; Berenbaum, Francis; Ladel, Christoph H.; Loef, Marieke; Lafeber, Floris P.J.G.; Welsing, Paco M.J.; Mastbergen, Simon C.; Roemer, Frank W. (AME, 2023-05)
      [Abstract] In the Innovative Medicine’s Initiative Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) knee osteoarthritis (OA) study, machine learning models were trained to predict the ...
    • Macro-Scale Spatial Modeling Reveals the Role of Soil Organic Matter Quality in CO2 Emissions 

      Tavanti, Renan; Lado, Marcos; Soares, Matheus Bortolanza; Trevisan, Rodrigo; Tavanti, Tauan Rimoldi; Freddi, Onã; Montanari, Rafael; Paz-González, Antonio (Elsevier, 2023-08-04)
      [Abstract] Carbon dioxide (CO2) emissions from agricultural soils result from the interaction of various factors that regulate the quantity and quality of organic material. Our objective was to assess changes in soil CO2 ...
    • Macrocyclic receptor showing improved PbII/ZnII and PbII/CaII selectivities 

      Ferreirós-Martínez, Raquel; Platas-Iglesias, Carlos; Blas, Andrés de; Esteban-Gómez, David; Rodríguez-Blas, Teresa (Wiley, 2010-05-31)
      [Abstract] Herein we report on the macrocyclic receptor N,N′‐bis[(6‐carboxy‐2‐pyridyl)methyl]‐1,10‐diaza‐15‐crown‐5 (H2bp15c5) and its coordination properties towards ZnII, CdII, PbII, and CaII. The stability constants of ...
    • El maestro en Educación Infantil ante la educación inclusiva: competencias y necesidades 

      Rebollo-Quintela, Nuria; Losada-Puente, Nuria (Universidad de Granada, 2023-01-31)
      [Resumen] La formación inicial del profesorado (FIP) debe estudiarse de acuerdo con la realidad cambiante y diversa de las escuelas. La capacitación de futuros docentes en educación infantil dependerá de su dominio de ...