Prediction Models
Mostrando 1-12 de 717 artigos, teses e dissertações.
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1. Encoding of Luminescent Ink Markers Using Low-Level Data Fusion and Chemometrics
The identification and analysis of documentary fraud is always a challenge for forensic science. Document analysis has proven to be an important branch of forensics in elucidating the authenticity of documents. The development and incorporation of luminescent inks in authentic documents have proved to be an excellent security feature. This paper purposes the
Journal of the Brazilian Chemical Society. Publicado em: 2023
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2. Growth phenotypes of very low birth weight infants for prediction of neonatal outcomes from a Brazilian cohort: comparison with INTERGROWTH
Abstract Objective: To assess the predictive value of selected growth phenotypes for neonatal morbidity and mortality in preterm infants < 30 weeks and to compare them with INTERGROWTH-21st (IG21). Methods: Retrospective analysis of data from the Brazilian Neonatal Research Network (BNRN) database for very low birth weight (VLBW) at 20 public tertiary-care
Jornal de Pediatria. Publicado em: 2023
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3. Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
In this work we developed a promising analytical method combining Fourier transform near-infrared (FT-NIR) spectroscopic technique and first-order multivariate calibration using partial least-squares (PLS) model to simultaneously quantify the main greenhouse gases (GHG’s): methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O) and water vapor (H2O). The
Journal of the Brazilian Chemical Society. Publicado em: 2022
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4. Rapid Recognizing the Producing Area of a Tobacco Leaf Using Near-Infrared Technology and a Multi-Layer Extreme Learning Machine Algorithm
A novel recognition method was put forward to identify the producing areas of the flue-cured tobacco leaves rapidly and non-destructively by using a near-infrared (NIR) spectrometer and a multi-layer-extreme learning machine (ML-ELM) algorithm. In contrast to traditional linear discriminant analysis (LDA) and extreme learning machine (ELM) algorithms, the ac
Journal of the Brazilian Chemical Society. Publicado em: 2022
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5. Temporal progression of sepsis on critical care COVID-19 patients: a retrospective cohort study
SUMMARY OBJECTIVE: This study aimed to describe sepsis progression in critical COVID-19 patients using the SOFA score and investigate its relationship with mortality. METHODS: Three researchers collected and analyzed retrospective clinical and laboratory data found in electronic health records from all patients admitted to a severe COVID-19 exclusive inten
Revista da Associação Médica Brasileira. Publicado em: 2022
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6. MLA and optical microscopy as complementary techniques to the iron ore geometallurgical studies
Abstract Mineral liberation is an important variable to be considered in the iron ore geometallurgical studies, especially since it provides information leading to the understanding of the ore’s behaviour in the beneficiation process, mainly when harder ores are concerned. Nowadays, the professionals and researchers in the mineral industry have been using
REM - International Engineering Journal. Publicado em: 2022
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7. Is Mallampati classification a good screening test? A prospective cohort evaluating the predictive values of Mallampati test at different thresholds
Abstract Background There is currently some discussion over the actual usefulness of performing preoperative upper airway assessment to predict difficult airways. In this field, modified Mallampati test (MMT) is a widespread tool used for prediction of difficult airways showing only a feeble predictive performance as a diagnostic test. We therefore aimed at
Brazilian Journal of Anesthesiology. Publicado em: 2022
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8. Derivation and validation of a national multicenter mortality risk stratification model - the ExCare model: a study protocol
Abstract Introduction Surgical care is essential for proper management of various diseases. However, it can result in unfavorable outcomes. In order to identify patients at higher risk of complications, several risk stratification models have been developed. Ideally, these tools should be simple, reproducible, accurate, and externally validated. Unfortunate
Brazilian Journal of Anesthesiology. Publicado em: 2022
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9. Predictive model for difficult laryngoscopy using machine learning: retrospective cohort study
Abstract Background Both predictions and predictors of difficult laryngoscopy are controversial. Machine learning is an excellent alternative method for predicting difficult laryngoscopy. This study aimed to develop and validate practical predictive models for difficult laryngoscopy through machine learning. Methods Variables for the prediction of difficul
Brazilian Journal of Anesthesiology. Publicado em: 2022
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10. Lung cancer screening in clinical practice: identification of high-risk chronic obstructive pulmonary disease patients
SUMMARY OBJECTIVE: The NELSON study demonstrated a positive association between computed tomography scanning and reduced mortality associated with lung cancer. The COPD-LUCSS-DLCO is a tool designed to improve screening selection criteria of lung cancer for chronic obstructive pulmonary disease patients. The aim of this study was to examine and compare the
Revista da Associação Médica Brasileira. Publicado em: 2022
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11. ASSESSMENT OF SOIL LOSS SUSCEPTIBILITY IN SANTA RITA WATERSHED IN SOUTHERN BRAZIL
ABSTRACT Estimation of soil loss susceptibility is of great importance for the management of watersheds. Thus, several models for soil loss prediction have been proposed. This study estimated the total annual soil loss for the Santa Rita watershed, located in southern Brazil, using the Revised Universal Soil Loss Equation. In addition, a classification to so
Eng. Agríc.. Publicado em: 2021-08
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12. On the Use of UTD-Based Models for RF Path Loss Prediction Due to Diffraction on a Forest-Covered Ridge
Abstract Irregular terrains covered with forest vegetation represent a challenging scenario for radio planning. A case of particular interest is the one where a forest-covered high hill or mountain is interposed to the link, for which typical diffraction loss models usually apply as good approximations, even disregarding the vegetation influence. Pragmatic a
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2021-06