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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 ...
Prediction of Nucleoitide Binding Peptides Using Star Graph Topological Índices
(Elsevier, 2015-08-05)
[Abstract] The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this ...
Needs, demands and reality of people with neuromuscular disorders users of wheelchair
(Crimson, 2017-11-13)
Background: The progressive nature of neuromuscular disease (NMD) results in a reduction in mobility: a person’s ability to move about, or
locomotion. Wheelchair is an assistive technology device (AT) that is fundamental ...
Mapping chemical structure-activity information of HAART-drug cocktails over complex networks of AIDS epidemiology and socioeconomic data of U.S. counties
(Elsevier, 2015-04-24)
[Abstract] Using computational algorithms to design tailored drug cocktails for highly active antiretroviral therapy (HAART) on specific populations is a goal of major importance for both pharmaceutical industry and public ...
Net-net Auto machine learning (AutoML) prediction of complex ecosystems
(Nature, 2018-08-17)
[Abstract] Biological Ecosystem Networks (BENs) are webs of biological species (nodes) establishing trophic relationships (links). Experimental confirmation of all possible links is difficult and generates a huge volume ...
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 ...
Early Warning in Egg Production Curves from Commercial Hens: a SVM Approach
(Elsevier, 2016-01-02)
[Abstract] Artificial Intelligence allows the improvement of our daily life, for instance, speech and handwritten text recognition, real time translation and weather forecasting are common used applications. In the livestock ...
Artificial Neural Networks Manipulation Server: Research on the Integration of Databases and Artificial Neural Networks
(Springer U K, 2002-06)
This paper proposes a new whole and distributed integration approach between Artificial Neural Networks (ANNs) and Databases (DBs) taking into account the different stages of the former’s lifecycle (training, test and ...
A generalized linear model for cardiovascular complications prediction in PD patients
(ACM, 2018)
[Abstract] This study was conducted using machine learning models to identify patient non-invasive information for cardiovascular complications prediction in peritoneal dialysis patients. Nowadays is well known that ...
ANN multiscale model of anti-HIV Drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks
(American Chemical Society, 2014)
[Abstract] This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The ...