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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 ...
Random Forest-Based Prediction of Stroke Outcome
(Nature Research, 2021)
[Abstract] We research into the clinical, biochemical and neuroimaging factors associated with the outcome of stroke patients to generate a predictive model using machine learning techniques for prediction of mortality and ...
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 ...
Carbapenem Resistance in Acinetobacter nosocomialis and Acinetobacter junii Conferred by Acquisition of blaOXA-24/40 and Genetic Characterization of the Transmission Mechanism between Acinetobacter Genomic Species
(American Society for Microbiology, 2022)
[Abstract] Carbapenem resistance is increasing among Gram-negative bacteria, including the genus Acinetobacter. This study aimed to characterize, for the first time, the development of carbapenem resistance in clinical ...
Wi-Fi Handshake: analysis of password patterns in Wi-Fi networks
(PEERJ INC, 2022)
[Abstract]: This article seeks to provide a snapshot of the security of Wi-Fi access points in the metropolitan area of A Coruña. First, we discuss the options for obtaining a tool that allows the collection and storage ...
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 ...
MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products
(BMC, 2024-01-23)
[Absctract]: The enantioselective Brønsted acid-catalyzed α-amidoalkylation reaction is a useful procedure is for the production of new drugs and natural products. In this context, Chiral Phosphoric Acid (CPA) catalysts ...
Machine Learning Algorithms Reveals Country-Specific Metagenomic Taxa from American Gut Project Data
(NLM (Medline), 2021)
[Abstract] In recent years, microbiota has become an increasingly relevant factor for the understanding and potential treatment of diseases. In this work, based on the data reported by the largest study of microbioma in ...
Machine learning analysis of TCGA cancer data
(PeerJ Inc., 2021)
[Abstract] In recent years, machine learning (ML) researchers have changed their focus towards biological problems that are difficult to analyse with standard approaches. Large initiatives such as The Cancer Genome Atlas ...
Machine Learning Analysis of the Human Infant Gut Microbiome Identifies Influential Species in Type 1 Diabetes
(Elsevier, 2021)
[Abstract] Diabetes is a disease that is closely linked to genetics and epigenetics, yet mechanisms for clarifying the onset and/or progression of the disease have sometimes not been fully managed. In recent years and due ...