204,674 results for machine learning
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Journal Article
Machine Learning in Acute Ischemic Stroke Neuroimaging
Machine Learning (ML) through pattern recognition algorithms is currently becoming an essential aid for the diagnosis, treatment, and prediction of complications and patient outcomes in a number of neurological diseases. The evaluation and treatment of Acute Ischemic Stroke (AIS) have experienced a…
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Journal Article
Vickers hardness prediction from machine learning methods
…or require coding knowledge. In this investigation, we built a successful machine learning model that implements Gradient Boosting Regressor (GBR) to predict hardness and uses the mechanical properties of a solid (bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio) as input…
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Journal Article
Combating small-molecule aggregation with machine learning
…neural network to flag such entities. Our data demonstrate the utility of machine learning for predicting SCAMs, achieving 80% of correct predictions in an out-of-sample evaluation. The tool is competitive with a panel of expert chemists, who correctly predict 61% ± 7% of the same molecules in a…
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Journal Article
Agricultural Crop Yield Prediction Using Machine Learning
Crop yield prediction is addressed through machine learning. Two predictor variables were used: hectares harvested, and production in tons. For the first case, the best model was a dense neural network (DNN) architecture, with a MSE of 0.0081, followed by Random Forest (RF) with an MSE of 0.0104…
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Journal Article
Predicting genome-wide redundancy using machine learning
…and lend insights into the evolutionary outcomes of gene duplication. Machine learning techniques are well suited to classifying gene family members into redundant and non-redundant gene pairs in model species where sufficient genetic and genomic data is available, such as Arabidopsis thaliana, the…
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Journal Article
Using Machine Learning to Analyze Merger Activity
…of artificial intelligence in finance and numerous other industries. Machine learning is used in process automation, security, underwriting and credit scoring, algorithmic trading and robo-advisory. In fact, machine learning AI applications are purported to save banks an estimated $447 billion by…
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Journal Article
Power of data in quantum machine learning
Expectations for quantum machine learning are high, but there is currently a lack of rigorous results on which scenarios would actually exhibit a quantum advantage. Here, the authors show how to tell, for a given dataset, whether a quantum model would give any prediction advantage over a classical…
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Journal Article
Advancing agricultural research using machine learning algorithms
Abstract Rising global population and climate change realities dictate that agricultural productivity must be accelerated. Results from current traditional research approaches are difficult to extrapolate to all possible fields because they are dependent on specific soil types, weather conditions…
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Journal Article
Rumors Detection Based on Lifelong Machine Learning
The amount of training data is small in the field of Weibo rumor detection, and online news changes constantly, but the existing models do not have the ability of continuous learning, which means they cannot achieve knowledge accumulation and update. Hence, they will require many training examples…
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Journal Article
Machine‐Learning Microstructure for Inverse Material Design
…for alloy design in the artificial intelligence era. Here, a successful machine‐learning (ML) method has been developed to identify the microstructure images with eye‐challenging morphology for a number of martensitic and ferritic steels. Assisted by it, a new neural‐network method is proposed for…
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Journal Article
Machine Learning Phases of Strongly Correlated Fermions
Machine learning offers an unprecedented perspective for the problem of classifying phases in condensed matter physics. We employ neural-network machine learning techniques to distinguish finite-temperature phases of the strongly correlated fermions on cubic lattices. We show that a…
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Journal Article
Information-rich localization microscopy through machine learning
Single-molecule methods often rely on point spread functions that are tailored to interpret specific information. Here the authors use a neural network to extract complex PSF information from experimental images, and demonstrate this by classifying color and axial positions of emitters.
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Journal Article
Quantum machine learning with adaptive linear optics
We study supervised learning algorithms in which a quantum device is used to perform a computational subroutine – either for prediction via probability estimation, or to compute a kernel via estimation of quantum states overlap. We design implementations of these quantum subroutines using Boson…
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Journal Article
Machine learning estimation of tissue optical properties
Abstract Dynamic, in vivo measurement of the optical properties of biological tissues is still an elusive and critically important problem. Here we develop a technique for inverting a Monte Carlo simulation to extract tissue optical properties from the statistical moments of the spatio-temporal…
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Journal Article
Machine learning and earthquake forecasting—next steps
A new generation of earthquake catalogs developed through supervised machine-learning illuminates earthquake activity with unprecedented detail. Application of unsupervised machine learning to analyze the more complete expression of seismicity in these catalogs may be the fastest route to improving…
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Journal Article
(Machine) learning to do more with less
Abstract Determining the best method for training a machine learning algorithm is critical to maximizing its ability to classify data. In this paper, we compare the standard “fully supervised” approach (which relies on knowledge of event-by-event truth-level labels) with a recent proposal that…
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Journal Article Full text
Keratoconus severity identification using unsupervised machine learning.
We developed an unsupervised machine learning algorithm and applied it to big corneal parameters to identify and monitor keratoconus stages. A big dataset of corneal swept source optical coherence tomography (OCT) images of 12,242 eyes acquired from SS-1000 CASIA OCT Imaging Systems in multiple…
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Journal Article Full text
MACHINE LEARNING AND IOT FOR SMART GRID
…elements, harnessing the science of Artificial Intelligence (AI) and Machine Learning (ML) methods become better used than before for prediction of energy consumption. In this work we present the SG with their architecture, the IoT with the component architecture and the Smart Meters (SM) which…
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Journal Article
A Survey of Topological Machine Learning Methods
…to be effective in supporting, enhancing, and augmenting both classical machine learning and deep learning models. In this paper, we review the state of the art of a nascent field we refer to as “topological machine learning,” i.e., the successful symbiosis of topology-based methods and machine…
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