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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 ...
Applying Artificial Intelligence for Operating System Fingerprinting
(MDPI, 2021)
[Abstract] In the field of computer security, the possibility of knowing which specific version of an operating system is running behind a machine can be useful, to assist in a penetration test or monitor the devices ...
Development of a Server for the Implementation of Data Processing Pipelines and ANN Training
(MDPI, 2021)
[Abstract] Data processing and the use of machine learning techniques make it possible to solve a wide variety of problems. The great disadvantage of using this type of technology is the enormous amount of computation ...
Detection of Chocolate Properties Using Near-Infrared Spectrophotometry †
(MDPI, 2021)
[Abstract] Knowing the chemical composition of a substance provides valuable information about it. That is why numerous techniques have been developed to try to obtain it. One of them is the Near Infrared Spectrometry ...
Design of Machine Learning Models for the Prediction of Transcription Factor Binding Regions in Bacterial DNA
(MDPI, 2021)
[Abstract] Transcription Factors (TFs) are proteins that regulate the expression of genes by binding to their promoter regions. There is great interest in understanding in which regions TFs will bind to the DNA sequence ...
Prediction of Peptide Vascularization Inhibitory Activity in Tumor Tissue as a Possible Target for Cancer Treatment
(M D P I AG, 2019-07-31)
[Abstract]The prediction of metabolic activities in silico form is crucial to be able to address all research possibilities without exceeding the experimental costs. In particular, for cancer research, the prediction of ...
Integrative Multi-Omics Data-Driven Approach for Metastasis Prediction in Cancer
(ACM, 2018)
[Abstract]
Nowadays biomedical research is generating huge amounts of omic data, covering all levels of genetic information from nucleotide sequencing to protein metabolism. In the beginning, data were analyzed independently ...
Gene Signatures Research Involved in Cancer Using Machine Learning
(M D P I AG, 2019)
[Abstract] With the cheapening of mass sequencing techniques and the rise of computer technologies, capable of analyzing a huge amount of data, it is necessary nowadays that both branches mutually benefit. Transcriptomics, ...
Identification of Prevotella, Anaerotruncus and Eubacterium Genera by Machine Learning Analysis of Metagenomic Profiles for Stratification of Patients Affected by Type I Diabetes
(MDPI AG, 2020-08-27)
[Abstract]
Previous works have reported different bacterial strains and genera as the cause of different clinical pathological conditions. In our approach, using the fecal metagenomic profiles of newborns, a machine ...
Application of Artificial Neural Networks for the Monitoring of Episodes of High Toxicity by DSP in Mussel Production Areas in Galicia
(MDPI AG, 2020-08-19)
[Abstract]
This study seeks to support, through the use of Artificial Neural Networks (ANN), the decision to perform closings after days without sampling in the Vigo estuary. The opening and closing of the mussel production ...