Artículos de Revistas

URI permanente para esta colección

https://repositorio.uft.cl/handle/20.500.12254/2436

Examinar

Examinando Artículos de Revistas por Materia "07 - Protección y mejora de la salud humana"

Mostrando 1 - 5 de 5
  • Miniatura
    Ítem
    A bi-objective optimization model to plan vaccination campaigns aided by temporary centers
    (Wiley, 2026) Montenegro-Dos Santos, Fernando
    Vaccination campaigns have saved thousands of lives and reached even the world’s most remote areas. However, the COVID-19 pandemic significantly changed the strategies for such campaigns. It is now crucial to rigorously consider new factors when planning the operational aspects of these campaigns, particularly for last-mile vaccine dispensing. First, a large share of the population must be vaccinated, with emphasis on vulnerable groups at higher risk. Second, if the virus is highly contagious and capable of asymptomatic transmission, implementing public health measures at vaccination sites becomes paramount. To address these challenges, we propose a bi-objective optimization model to support healthcare decision-making. It defines a schedule for locating temporary vaccination centers and assigning populations to permanent and temporary sites over a planning horizon. Moreover, we formalize and validate a minimum set of properties for a function-based prioritization mechanism to ensure consistent prioritization. One objective prioritizes vaccinating vulnerable groups according to our novel function-based approach, while the other minimizes the operational costs of temporary centers. In the complex environment of a pandemic, the strategic integration and use of temporary and permanent vaccination centers is vital for creating a robust and responsive vaccination strategy. Temporary centers, whose locations are determined by the model, improve access for hard-to-reach groups, contribute to minimizing crowding at permanent sites, and lower infection risks. Our results, demonstrated through a case study, show that the model effectively allocates resources and generates various vaccination plans that cater to different priority levels assigned to each objective, thereby offering valuable decision support.
  • Miniatura
    Ítem
    Design of an EEG analytical methodology for the analysis and interpretation of cerebral connectivity signals
    (Elsevier, 2021-02-20) Córdova, Felisa M.
    The objective of this study is to design an Electroencephalographic (EEG) analytic methodology that allows to develop a variety of analysis and interpretations of brain signals. The initial phase considers the acquisition and filtering of EEG signals, the division into bands in data ranges, and the storage of EEG signals in a cloud data base. Then, an analytical phase considering descriptive, predictive and prescriptive analysis is accomplished. A sequence of analytic intermediate processing steps is done in order to render a graphic visualization of significant correlations between pairs of EEG channels. Pearson correlation is utilized to detect synchronic connectivity through the brain areas. Time series in nearly instantaneous time lapses are treated by using Hilbert Huang Transform. An experimental design by submitting a set of students to an abbreviated version Raven visual test is made providing results in correlation maps of cerebral connectivity
  • Miniatura
    Ítem
    ML models for severity classification and length-of-stay forecasting in emergency units
    (Elsevier, 2023-03-02) Candia-Véjar, Alfredo
    Length-of-stay (LoS) prediction and severity classification for patients in emergency units in a clinic or hospital are crucial problems for public and private health networks. An accurate estimation of these parameters is essential for better planning resources, which are usually scarce. Although it is possible to find several works that propose traditional Machine Learning (ML) models to face these challenges, few works have exploited advances in Natural Language Processing (NLP) on Spanish raw-text vector representations. Consequently, we take advantage of those advances, incorporating sentence embeddings in traditional ML models to improve predictions. Moreover, we apply a strategy based on SHapley Additive exPlanations (SHAP) values to provide explanations for these predictions. The results of our case study demonstrate an increase in the accuracy of the predictions using raw text with a minimum preprocessing. The precision increased by up to 2% in the classification of the patient’s post-care destination and by up to 8% in the prediction of LoS in the hospital. This evidence encourages practitioners to use available text to anticipate the patient’s need for hospitalization more accurately at the earliest stage of the care process.
  • Miniatura
    Ítem
    Profiling and characterization of plant-based products consumers in Chile
    (Asociación Castellano-Manchega de Sociología (ACMS), 2024-12-14) Campos, Zócimo
    The consumption trend of plant-based products has increased worldwide due to different reasons, and Chile has been a good example of this trend. Although sustainability, health, nutrition and taste may all seem to be main drivers for flexitarians seeking plant-based food and beverages, to date there is no research that allows characterizing and profiling Chilean consumers of plant-based products. Hence, this work seeks to close this gap. To address this problem, we conducted an online survey of 512 people, mainly focused on the Metropolitan Region and Valparaíso. Using Ward’s method, we identified 3 clusters: (1) Animal friendly, (2) Planet friendly and (3) Healthy lifestyle, where, respectively, animal welfare, care for the environment and concern for health are prioritized.
  • Miniatura
    Ítem
    UiO-66(Zr) as drug delivery system for non-steroidal anti-inflammatory drugs
    (Elsevier, 2024-06-06) Salazar, Javier
    The toxicity for the human body of non-steroidal anti-inflammatory drugs (NSAIDs) overdoses is a consequence of their low water solubility, high doses, and facile accessibility to the population. New drug delivery systems (DDS) are necessary to overcome the bioavailability and toxicity related to NSAIDs. In this context, UiO-66(Zr) metal-organic framework (MOF) shows high porosity, stability, and load capacity, thus being a promising DDS. However, the adsorption and release capability for different NSAIDs is scarcely described. In this work, the biocompatible UiO-66(Zr) MOF was used to study the adsorption and release conditions of ibuprofen, naproxen, and diclofenac using a theoretical and experimental approximation. DFT results showed that the MOF-drug interaction was due to an intermolecular hydrogen bond between protons of the groups in the defect sites, (μ3 − OH, and − OH2) and a lone pair of oxygen carboxyl functional group of the NSAIDs. Also, the experimental results suggest that the solvent where the drug is dissolved affects the adsorption process. The adsorption kinetics are similar between the drugs, but the maximum load capacity differs for each drug. The release kinetics assay showed a solvent dependence kinetics whose maximum liberation capacity is affected by the interaction between the drug and the material. Finally, the biological assays show that none of the systems studied are cytotoxic for HMVEC. Additionally, the wound healing assay suggests that the UiO-66(Zr) material has potential application on the wound healing process. However, further studies should be done.