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Published in 2024 at "Meccanica"
DOI: 10.1007/s11012-024-01797-z
Abstract: Combining machine learning (ML) with computational fluid dynamics (CFD) opens many possibilities for improving simulations of technical and natural systems. However, CFD+ML algorithms require exchange of data, synchronization, and calculation on heterogeneous hardware, making their…
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Keywords:
combining machine;
learning computational;
machine learning;
openfoam smartsim ... See more keywords
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Published in 2017 at "ACS nano"
DOI: 10.1021/acsnano.7b05503
Abstract: Circulating exosomes contain a wealth of proteomic and genetic information, presenting an enormous opportunity in cancer diagnostics. While microfluidic approaches have been used to successfully isolate cells from complex samples, scaling these approaches for exosome…
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Keywords:
machine learning;
pancreatic cancer;
combining machine;
learning nanofluidic ... See more keywords
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Published in 2022 at "Studies in health technology and informatics"
DOI: 10.3233/shti210965
Abstract: This study analyzes samples of intestinal microbiome and metabolites, from healthy individuals (HE) and patients with adenomas (AD) or colorectal carcinomas (CRC). A network analysis (NetAn) method was applied to the data, to identify the…
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Keywords:
network;
machine learning;
combining machine;
learning network ... See more keywords
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Published in 2025 at "Agriculture"
DOI: 10.3390/agriculture15050494
Abstract: Combining machine learning algorithms with Earth observations has great potential in the context of crop monitoring and management, which is essential in the face of global challenges related to food security and climate change [...]
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Keywords:
earth observations;
algorithms earth;
combining machine;
machine learning ... See more keywords