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scopus(3)
Prediction of healthcare associated infections in an intensive care unit using machine learning and big data tools
Conference ObjectAbstract: Healthcare associated infections (HAIS) can be acquired by patients during their stay in a hospital.Palabras claves:BIG DATA, Healthcare Associated Infections, Intensive Unit Care, Machine learning, RISK FACTORSAutores:Álvarez-Rodríguez J., Jose Luis Rojo-Álvarez, Ramos-Lpez J., Revuelta-Zamorano P., Sanchez A., Soguero-Ruiz C.Fuentes:scopusOntology for heart rate turbulence domain from the conceptual model of SNOMED-CT
ArticleAbstract: Electronic health record (EHR) automates the clinician workflow, allowing evidence-based decision suPalabras claves:Cardiovascular Risk, Conceptual model, electrocardiogram (ECG), electronic health recording(EHR), Heart rate turbulence (HRT), ontology, SNOMED-CTAutores:Barquero-Perez O., GarcÍa-Alberola A., Jose Luis Rojo-Álvarez, Lechuga-Suarez L., Mora-Jimnez I., Ramos-Lpez J., Soguero-Ruiz C.Fuentes:scopusTowards semantic interoperability for cardiovascular risk stratification into the electronic health records using archetypes and SNOMED-CT
Conference ObjectAbstract: Clinical data exchange among different organizations can be of great value in the field of CardiovasPalabras claves:Autores:GarcÍa-Alberola A., Jose Luis Rojo-Álvarez, Lechuga L., Mora-Jimnez I., Ramos-Lpez J., Sánchez-Caro A., Serrano-Balazote P., Soguero-Ruiz C.Fuentes:scopus