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Markov Mean Properties for Cell Death-Related Protein Classification
(Elsevier, 2014-01-31)
[Abstract] The cell death (CD) is a dynamic biological function involved in physiological and pathological processes. Due to the complexity of CD, there is a demand for fast theoretical methods that can help to find new ...
Experimental study and random forest prediction model of microbiome cell surface hydrophobicity
(Elsevier, 2016-11-09)
[Abstract] The cell surface hydrophobicity (CSH) is an assessable physicochemical property used to evaluate the microbial adhesion to the surface of biomaterials, which is an essential step in the microbial biofilm formation ...
Classification of mild cognitive impairment and Alzheimer’s Disease with machine-learning techniques using 1H Magnetic Resonance Spectroscopy data
(Elsevier, 2015-03-30)
[Abstract] Several magnetic resonance techniques have been proposed as non-invasive imaging biomarkers for the evaluation of disease progression and early diagnosis of Alzheimer’s Disease (AD). This work is the first ...
Applied Computational Techniques on Schizophrenia Using Genetic Mutations
(Bentham, 2013-03-01)
[Abstract] Schizophrenia is a complex disease, with both genetic and environmental influence. Machine learning techniques can be used to associate different genetic variations at different genes with a (schizophrenic or ...
Authentication of tequilas using pattern recognition and supervised classification
(Elsevier, 2017-07-18)
[Abstract] Sales of reputed, Mexican tequila grown substantially in last years and, therefore, counterfeiting is increasing steadily. Hence, methodologies intended to characterize and authenticate commercial beverages are ...
A methodology for the design of experiments in computational intelligence with multiple regression models
(Peer J, 2016-12-01)
[Abstract] The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the ...
Visual complexity modelling based on image features fusion of multiple kernels
(PeerJ, Ltd., 2019-07-18)
[Abstract] Humans’ perception of visual complexity is often regarded as one of the key principles of aesthetic order, and is intimately related to the physiological, neurological and, possibly, psychological characteristics ...
Comparison of Outlier-Tolerant Models for Measuring Visual Complexity
(MDPI AG, 2020-04-24)
[Abstract] Providing the visual complexity of an image in terms of impact or aesthetic preference can be of great applicability in areas such as psychology or marketing. To this end, certain areas such as Computer Vision ...
Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques
(PeerJ, Ltd., 2020-07-27)
[Abstract]
Food consumption patterns have undergone changes that in recent years have resulted in serious health problems. Studies based on the evaluation of the nutritional status have determined that the adoption of a ...
A review on machine learning approaches and trends in drug discovery
(Research Network of Computational and Structural Biotechnology, 2021)
Abstract: Drug discovery aims at finding new compounds with specific chemical properties for the treatment of diseases. In the last years, the approach used in this search presents an important component in computer science ...