359.866 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
Machine learning–accelerated computational fluid dynamics
…trade-offs between accuracy and tractability. Here we use end-to-end deep learning to improve approximations inside computational fluid dynamics for modeling two-dimensional turbulent flows. For both direct numerical simulation of turbulence and large-eddy simulation, our results are as accurate as…
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Machine Learning for Cancer Drug Combination
When treating multiple complex diseases, such as cancer, polytherapy may demonstrate efficiency than monotherapy. However, due to the multiplicative relationship between the number of drugs and cell lines vs. the number of combinations, it is impractical to test all drug combinations using…
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Machine Learning Identification of Piezoelectric Properties
…for manufacturers and end users. In this paper, we present the use of a machine learning approach to determine the parameters in the model. In this first work, the main sensitive parameters, c(11), c(13), c(33), c(44) and e(33) were predicted using a neural network numerically trained by using…
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Regulatory responses to medical machine learning
Companies and healthcare providers are developing and implementing new applications of medical artificial intelligence, including the artificial intelligence sub-type of medical machine learning (MML). MML is based on the application of machine learning (ML) algorithms to automatically identify…
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Predicting Kidney Discard using Machine Learning
BACKGROUND. Despite kidney supply shortage, 18%−20% deceased donor kidneys are discarded annually in the US. In 2018, 3,569 kidneys were discarded. METHODS. We compared Machine Learning (ML) techniques to identify kidneys at risk of discard at the time of match-run, and after biopsy and machine…
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Machine learning applications in radiation oncology
Machine learning technology has a growing impact on radiation oncology with an increasing presence in research and industry. The prevalence of diverse data including 3D imaging and the 3D radiation dose delivery presents potential for future automation and scope for treatment improvements for…
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Predicting glycosylation stereoselectivity using machine learning
Predicting the stereochemical outcome of chemical reactions is challenging in mechanistically ambiguous transformations. The stereoselectivity of glycosylation reactions is influenced by at least eleven factors across four chemical participants and temperature. A random forest algorithm was trained…
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Machine learning in combinatorial polymer chemistry
The design of new functional polymers depends on the successful navigation of their structure-function landscapes. Advances in combinatorial polymer chemistry and machine learning provide exciting opportunities for the engineering of fit-for-purpose polymeric materials.
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Predicting Bitcoin Prices Using Machine Learning
In this paper we predict Bitcoin movements by utilizing a machine-learning framework. We compile a dataset of 24 potential explanatory variables that are often employed in the finance literature. Using daily data from 2nd of December 2014 to July 8th 2019, we build forecasting models that utilize…
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Quantum machine learning with differential privacy
Quantum machine learning (QML) can complement the growing trend of using learned models for a myriad of classification tasks, from image recognition to natural speech processing. There exists the potential for a quantum advantage due to the intractability of quantum operations on a classical…
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Machine Learning-Enhanced Flexible Mechanical Sensing
…complicated data collected by a single sensor or network of sensors. Machine learning (ML) as an important branch of artificial intelligence can efficiently handle such complex data, which can be multi-dimensional and multi-faceted, thus providing a powerful tool for easy interpretation of sensing…
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Machine Learning for Precision Epilepsy Surgery
…the clinical need, the relevant computational science focusing on machine learning, and discusses some specific applications in epilepsy surgery.
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Artikel Jurnal Teks lengkap
Sparse Machine Learning in Banach Spaces
…mathematics, statistics and engineering the fundamental concept of sparse machine learning in Banach spaces. In particular, we use binary classification as an example to explain the essence of learning in a reproducing kernel Hilbert space and sparse learning in a reproducing kernel Banach space…
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