Publications by authors named "Xiomara Patricia Blanco-Valencia"
Introduction: Immunosuppression (IS) determines a higher risk of disease severity from LM) infection.
Methods: We examined the epidemiology of IS in all patients hospitalized with LM in Spain from 2000 to 2021 in the National Registry of Hospital Discharges. IS was defined by liver disease (LD), diabetes mellitus (DM), chronic kidney disease (CKD), solid organ transplantation (SOT), bone marrow transplantation (BMT), primary immunodeficiencies (ID), systemic autoimmune diseases (SAD), solid organ neoplasms (SON), and hematological neoplasms (HN).
Pregnancy-related listeriosis in Spain.
J Infect Public Health
February 2025
Background: Pregnant women are at high risk of acquiring listeriosis, resulting in severe fetal and neonatal outcomes.
Methods: All hospitalizations with a listeriosis diagnosis in pregnant women (obstetric listeriosis) and/or newborns (neonatal listeriosis) in Spain from 2000 to 2021 were examined using the National Registry of Hospital Discharges, employing ICD-9 and -10 coding lists.
Results: A total of 540 and 450 hospital admissions for obstetric listeriosis and neonatal listeriosis were identified, respectively, with 146 adverse fetal-neonatal outcomes (miscarriage, fetal loss, stillbirth, and neonatal death).
Background: The higher mortality rates in patients with Systemic sclerosis (SSc) are related to SSc activity, cardiovascular disease, and neoplasms, among other factors. Our objective was to assess the impact of solid organ neoplasms (SON) and hematological neoplasms (HN) on mortality among SSc patients.
Methods: A retrospective, observational comparison of SON and HN-related deaths in SSc patients with those in the general Spanish population was conducted using data from the Spanish Hospital Discharge Database.
Article Synopsis
- Facial emotion recognition (FER) is important for applications like human-computer interaction and emotion detection, but current methods struggle with accuracy.
- The paper introduces a new framework called extended walrus-based deep learning with Botox feature selection network (EWDL-BFSN) that aims to accurately detect facial emotions by optimizing feature selection and classifier parameters.
- The EWDL-BFSN model uses advanced techniques like gradient wavelet anisotropic filtering and SqueezeNet for feature extraction, achieving impressive accuracy rates of 99.37% and 99.25% on the CK+ and FER-2013 datasets, outperforming existing methods.