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Se presentan resultados obtenidos de la predicción de varios parámetros claves, como la velocidad de onda de pulso, relacionados a la salud cardiovascular utilizando un modelo unidimensional (1-D) como parte del entrenamiento de los modelos de aprendizaje automático, así como también la verificación de dichas predicciones utilizando señales reales obtenidas de un protocolo de medición.

Liver transplantation is the last therapeutic option in patients with end-stage liver diseases. The adequate clinical management of transplant-patients impacts their vital prognosis and decisions on many occasions are made from the interaction of multiple variables involved in the process. This work is based on the National Liver Transplantation Program in Uruguay. We performed predictive analysis of cardiometabolic diseases on the transplanted cohort between 2014 and 2019, considering vascular age as a key factor. This aims at classification of the cohort based on the vascular age of the evaluated patients before transplantation for risk-profiling. Predicted high-risk group of the patients showed substantial deterioration of post-transplant health-conditions, including higher mortality rate. In our knowledge, this is the first study in Latin America incorporating vascular age toward predictive analysis of cardiometabolic risk factors in liver transplantations. Predictive risk-modeling using vascular age in a pre-transplantation scenario provides significant opportunity for early prediction of post-transplant risk factors, leading to efficient treatment with anticipation.

Allometry describes the disproportionate changes in shape, size or function that are observed when comparing separate isolated features in animals spanning a range of body sizes. Scaling of the energy dissipation has been also observed in warm blooded animals, essentially varying as mammal's body mass (BM). Part of the energy stored in the arterial wall during elastic distension corresponding to the viscous deformation is dissipated within the arterial wall.To elucidate the allometric existing relationship between BM and arterial wall viscosity, as a measure of energy dissipation.Arterial viscous dissipation (WAn allometric law was found between WThe existence of a power-law link for viscous dissipation and BM that involve different mammals was demonstrated.

A deep learning technique based on semantic segmentation was implemented into the blood pressure detection points field. Two models were trained and evaluated in terms of a reference detector. The proposed methodology outperforms the reference detector in two of the three classic benchmarks and on signals from a public database that were modified with realistic test maneuvers and artifacts. Both models differentiate regions with valid information and artifacts. So far, no other delineator had shown this capacity.