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Mostrando publicaciones 1-10 de 20
Strategy based on data mining and MALDI-Mass spectrometry for control disease of SRS in Salmo Salar
(2018)
Piscirickettsia salmonis is a highly transmissible pathogens that cause high mortality in farmed salmonids. In this way, new techniques based on mass spectrometry (MS) and machine learning were applied and combined in an ...
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 ...
Risk assessment tools and data-driven approaches for predicting and preventing suicidal behavior
(2019)
Risk assessment of suicidal behavior is a time-consuming but notoriously inaccurate activity for mental health services globally. In the last 50 years a large number of tools have been designed for suicide risk assessment, ...
X-MassFP: a platform with focus on pattern research for mass spectrometry fingerprint recognition
(2021)
Pathogens are infectious microorganisms that lodge in a host and are responsible for causing diseases. In many cases, the detection of pathogens is expensive in resources and time. In this way, mass spectrometry is combined ...
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 ...
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 ...
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 ...
A new fast training algorithm for autoencoder neural networks based on extreme learning machine
(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 ...
Patients at high risk of suicide before and during a COVID-19 lockdown: ecological momentary assessment study
(2021)
The coronavirus disease 2019 (COVID-19) outbreak may have affected the mental health of patients at high risk of suicide. In this study we explored the wish to die and other suicide risk factors using smartphone-based ...
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. ...