CRIS :: Universidad UTE

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A newly isolated Scenedesmus bijugus PY6 for high-valued astaxanthin production via two-stage heterotrophic cultivation
(Elsevier BV, 2026-08)
Liu, Pingying
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Xiao, Xuehua
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Zhou, Youcai
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Guo, Xu
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Zhou, Dahui
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Energy Efficiency and Environmental Nexus: An Assessment for the Efficient Reduction of Carbon Dioxide Emissions
(Wiley, 2026-01)
Raza, Muhammad Amir
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Aman, Muhammad Mohsin
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Farooq, Muhammad
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NIZAMI , ABDUL SATTAR
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Khaliq, Jibran
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Landscape Genetics Reveals Geographic Structuring of Locally Adapted Goat Populations from Brazil, Spain, and Ecuador
(MDPI AG, 2026-05-15)
CASTILLO CEVALLOS, LUIS ANTONIO
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Rocha, Laura Leandro da
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Aguirre Riofrio, Edgar Lenin
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Martinez Martinez, Amparo
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Delgado Bermejo, Juan Vicente
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Perception of ChatGPT in University Students to Solve Mathematics Exercises
(Springer Nature Switzerland, 2026)
Bastidas-Chalán, Rodrigo
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Mantilla-Morales, Gisella
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Rentería-Torres, Aníbal
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VALENCIA ORDÓÑEZ, ULICES PAÚL
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Zambrano-Vera, Edwin
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CO2 conversion into fuels and value-added chemicals: from molten salt catalysts to metal–organic and covalent–organic frameworks
(Springer Science and Business Media LLC, 2026-04-27)
Liu, Lianteng
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Behmadi, Reza
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Tan, Rongrong
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Rahimi, Hamed
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Shoja Razavi, Reza
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Predicting early response to ablative radiotherapy in oligometastatic disease: a scoping review of radiomics-based machine learning and deep learning models
(Springer Science and Business Media LLC, 2026-04-30)
García-Pablo, Raquel
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Canela-Capdevila, Marta
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Martínez-Caballero, Alberto
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Benavides-Villareal, Rocío
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Moragas-Fernández, Albert
Objectives Oligometastatic disease represents an intermediate stage of cancer, often treated with surgery or ablative radiotherapy (ART). This scoping review aimed to systematically summarize current evidence on the use of radiomics, including machine learning and deep learning approaches, to predict response to ART. We also aimed to assess the methodological quality and reporting transparency of published studies, identifying gaps and opportunities for future research. Materials and methods A systematic search in PubMed, Web of Science, Scopus, Embase, Cochrane, and Google Scholar identified studies that used radiomics for predicting ART response. Two reviewers independently selected and assessed the methodological quality using the Radiomics Quality Score (RQS) and the METhodological RadiomICs Score (METRICS). In addition, reporting transparency was evaluated using the CheckList for EvaluAtion of Radiomics research (CLEAR). This scoping review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews guidelines. Results The systematic search identified 9463 records, of which 29 studies (3946 patients) were included. Most studies used MRI-derived features, with 24 focusing on brain metastases. Radiomics-based models demonstrated variable predictive performance (area under the curve, AUC: 0.69–0.95), with deep learning models achieving the highest accuracies (AUC: 0.85–1.00). Methodological quality of the studies was moderate (mean RQS: 13; METRICS: 64.2–78%). Conclusion Radiomics-based models show potential for identifying patients unlikely to benefit from ART, but their clinical implementation remains limited, especially for extracranial metastases. Future research should focus on multicenter, prospective studies with standardized protocols, incorporating clinical and dosimetric data for broader clinical application. Key Points Question Can radiomics-based predictive models reliably assess treatment response to ablative radiotherapy in oligometastatic disease, and how robust is the current methodological evidence supporting their use? Findings Radiomics models show encouraging predictive performance, mainly for brain metastases, yet substantial methodological heterogeneity and limited validation hinder their clinical translation. Clinical relevance Radiomics-based prediction models hold potential for identifying patients unlikely to benefit from ablative radiotherapy, enabling more personalized treatment. Further prospective, multicenter, and methodologically standardized studies are essential before clinical implementation.
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LEARNING STRATEGIES (ACRA) AMONG UNIVERSITY APPLICANTS FOR THE TOURISM DEGREE: A STRUCTURAL EQUATION MODELING AND NEURAL NETWORK APPROACH
(Ponteditora, 2025-05)
Peñate, Mikel
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Garcia, Angel
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Herrrera, Reinaldo
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Higuerey-Gómez, Angel
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Llanez, Elvia
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Nanobioremediation for sustainable wastewater management in smart cities: Advancements, challenges, and environmental benefits
(Elsevier BV, 2026-10)
HESAM, KAMYAB
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Khademi, Tayebeh
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Farajnezhad, Mohammad
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Khalili, Elham
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Yuzir, Ali
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2026 Latin American consensus for the management of patients with hypertension and cardio-renal and metabolic disturbances: endorsed by the Latin American Society of Hypertension, the Iberoamerican Hypertension League, and the World Hypertension League
(Ovid Technologies (Wolters Kluwer Health), 2026-03-17)
Coca, Antonio
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Sánchez, Ramiro
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Molina de Salazar, Dora I.
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Peñaherrera, Ernesto
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Alcocer, Luis
Scopus© Citations 1
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Sustainable production of aviation biofuel using wastewater-grown microalgae: Process optimization and life cycle assessment of scenario-based strategies
(Elsevier BV, 2026-11)
Purba, Laila Dina Amalia
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Effendi, Devi Bentia
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Kurniawan, Koko Iwan Agus
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Setiawan, Arief Ameir Rahman
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HESAM, KAMYAB
Scopus© Citations 3

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