Auflistung nach Schlagwort "machine learning"
Anzeige der Publikationen 1-6 von 6
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2023-05-12ZeitschriftenartikelCombination of whole genome sequencing and supervised machine learning provides unambiguous identification of eae-positive Shiga toxin-producing Escherichia coli Introduction: The objective of this study was to develop, using a genome wide machine learning approach, an unambiguous model to predict the presence of highly pathogenic STEC in E. coli reads assemblies derived from ...
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2020-01-23ZeitschriftenartikelDigitale Epidemiologie Digitale Epidemiologie ist ein relativ neues, rapide wachsendes Forschungsgebiet. Die technologische Revolution des letzten Jahrzehnts, die globale Vernetzung, der Informationsaustausch über soziale Medien und insbesondere ...
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2019-04-26ZeitschriftenartikeleDiVA—Classification and prioritization of pathogenic variants for clinical diagnostics Mendelian diseases have shown to be an and efficient model for connecting genotypes to phenotypes and for elucidating the function of genes. Whole‐exome sequencing (WES) accelerated the study of rare Mendelian diseases in ...
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2022-08-17ZeitschriftenartikelMachine Learning Algorithms for Classification of MALDI-TOF MS Spectra from Phylogenetically Closely Related Species Brucella melitensis, Brucella abortus and Brucella suis (1) Background: MALDI-TOF mass spectrometry (MS) is the gold standard for microbial fingerprinting, however, for phylogenetically closely related species, the resolution power drops down to the genus level. In this study, ...
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2021-05-31ZeitschriftenartikelReal-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection As several countries gradually release social distancing measures, rapid detection of new localized COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ...
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2021-05-26ZeitschriftenartikelSwarm Learning for decentralized and confidential clinical machine learning Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood ...