Listar Producción Académica por materia "Machine learning"
Mostrando publicaciones 1-20 de 25
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A deep learning approach to population structure inference in inbred lines of maize
(2020)Analysis of population genetic variation and structure is a common practice for genome-wide studies, including association mapping, ecology, and evolution studies in several crop species. In this study, machine learning ...
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A hybrid algorithm of ML and XAI to prevent breast cancer: a strategy to support decision making
(2023)Worldwide, the coronavirus has intensified the management problems of health services, significantly harming patients. Some of the most affected processes have been cancer patients’ prevention, diagnosis, and treatment. ...
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A new fast training algorithm for autoencoder neural networks based on extreme learning machine
; Mora, Marco
; ; ; ; (2022)
Autoencoders are neural networks that are characterized by having the same inputs and outputs. This kind of Neural Networks aim to estimate a nonlinear transformation whose parameters allow to represent the input patterns ...
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A novel strategy to classify chronic patients at risk: a hybrid machine learning approach
(2022)Various care processes have been affected by COVID-19. One of the most dramatic has been the care of chronic patients under medical supervision. According to the World Health Organization (WHO), a chronic patient has one ...
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A novel traffic prediction method using machine learning for energy efficiency in service provider networks
(2023)This paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main ...
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Academic performance predicting model based on machine learning and keller's motivation measure
(2022)This article investigates a model for predicting the academic performance of university students using Machine Learning techniques based on the level of motivation achieved with the implementation of the ARCS instructional ...
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Comparative lightweight scheme for individual identification through hand-vein patterns
(2024)Biometric characterization systems are generally used in safety-related applications because they allow the identification or verification of individuals based on human body traits. In recent years hand veins have become ...
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Engineering students' perception of the use of machine learning in accounting learning
(2022)This article investigates the effects on motivation and learning of topics related to the accounting subject, with theimplementation of Machine Learning as a pedagogical tool in the context of university education. A ...
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Enhanced epileptic seizure detection through wavelet-based analysis of EEG signal processing
(2024)Epilepsy affects millions worldwide, making timely seizure detection crucial for effective treatment and enhanced well-being. Electroencephalogram (EEG) analysis offers a non-intrusive solution, but its visual interpretation ...
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Examining the relationship between COVID-19 and suicide in media coverage through natural language processing analysis
(2024)Background and objectives Suicide is a major public health concern, media can influence its awareness, contagion, and prevention. In this study, we evaluated the relationship between the COVID-19 pandemic and suicide in ...
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Exploring blood-brain barrier passage using atomic weighted vector and machine learning
(2024)Context This study investigates the potential of leveraging molecular properties, as determined by MD-LOVIs software and machine learning techniques, to predict the ability of compounds to cross the blood–brain barrier ...
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Exploring the potential of emerging technologies as pedagogical tools for engineering education
(2023)The utilization of emerging technologies in the field of education has evolved into a valuable resource for fostering pedagogical advancements. Hence, the primary aim of this article is to assess and compare various ...
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Integrating machine learning with MALDI-TOF mass spectrometry for rapid and accurate antimicrobial resistance detection in clinical pathogens
(2025)Antimicrobial resistance (AMR) is one of the most pressing public health challenges of the 21st century. This study aims to evaluate the efficacy of mass spectral data generated by VITEK® MS instruments for predicting ...
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Machine learning and matrix-assisted laser desorption/ionization time-of-flight mass spectra for antimicrobial resistance prediction: a systematic review of recent advancements and future development
; ; ; Cuadros-Orellana, Sara (2024)
Background: The use of matrix-assisted laser desorption/ionization time-of-flight mass spectra (MALDI-TOF MS) combined with machine learning techniques has recently emerged as a method to address the public health crisis ...
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Machine learning approach for predicting corporate social responsibility perception in university students
(2023)Corporate Social Responsibility has become an important corporate principle. Perception about the use of this concept is regarded by corporate stakeholders as strategically crucial. The present work explores the use of ...
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Machine learning model for predicting primary school scores based on spatial, socio demographic and school–related information
(2024)Learning strategies at primary school level are important to ensure student progress. In this regards, the identification of those factors influencing students grades certainly help teachers in predicting outcomes as well ...
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Machine learning-based classifiers to predict metastasis in colorectal cancer patients
(2024)Background: The increasing prevalence of colorectal cancer (CRC) in Iran over the past three decades has made it a key public health burden. This study aimed to predict metastasis in CRC patients using machine learning ...
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Machine learning-driven classification of urease inhibitors leveraging physicochemical properties as effective filter criteria
(2024)Urease, a pivotal enzyme in nitrogen metabolism, plays a crucial role in various microorganisms, including the pathogenic Helicobacter pylori. Inhibiting urease activity offers a promising approach to combating infections ...
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Multi-label classification to predict antibiotic resistance from raw clinical MALDI-TOF mass spectrometry data
(2024)Antimicrobial resistance (AMR) poses a significant global health challenge, necessitating advanced predictive models to support clinical decision-making. In this study, we explore multi-label classification as a novel ...
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Optimizing hyperparameters in machine learning models for accurate fitness activity classification in school-aged children
(2024)Classification using machine learning algorithms in physical fitness tests carried out by students in educational centers can help prevent obesity and other related diseases. This research aims to evaluate physical fitness ...