214,423 results for machine learning
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The RSNA Pediatric Bone Age Machine Learning Challenge
PURPOSE: The Radiological Society of North America (RSNA) Pediatric Bone Age Machine Learning Challenge was created to show an application of machine learning (ML) and artificial intelligence (AI) in medical imaging, promote collaboration to catalyze AI model creation, and identify innovators in…
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Adapting machine-learning algorithms to design gene circuits
…models are complex systems with many parameters. In this work, we adapted machine-learning algorithms to significantly accelerate gene circuit discovery. RESULTS: We use gradient-descent optimization algorithms from machine learning to rapidly screen and design gene circuits. With this approach, we…
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Breast Cancer Prognosis Using a Machine Learning Approach
Machine learning (ML) has been recently introduced to develop prognostic classification models that can be used to predict outcomes in individual cancer patients. Here, we report the significance of an ML-based decision support system (DSS), combined with random optimization (RO), to extract…
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A machine learning approach for somatic mutation discovery
…this issue, we developed a somatic mutation discovery approach based on machine learning that outperformed existing methods in identifying experimentally validated tumor alterations (sensitivity of 97% versus 90 to 99%; positive predictive value of 98% versus 34 to 92%). Analysis of paired…
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Applying Machine Learning to Continuously Monitored Physiological Data
The use of machine learning (ML) in healthcare has enormous potential for improving disease detection, clinical decision support, and workflow efficiencies. In this commentary, we review published and potential applications for the use of ML for monitoring within the hospital environment. We…
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Text-mined fossil biodiversity dynamics using machine learning
…ages from unstructured text in books and scientific articles using machine-learning approaches. We use Bryozoa, a group of marine invertebrates with a rich fossil record, as a case study. Building on recent advances in computational linguistics, we develop a pipeline to recognize taxonomic names…
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Identification of Novel Antibacterials Using Machine Learning Techniques
Many pharmaceutical companies are avoiding the development of novel antibacterials due to a range of rational reasons and the high risk of failure. However, there is an urgent need for novel antibiotics especially against resistant bacterial strains. Available in silico models suffer from many…
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Artificial intelligence and machine learning in spine research
Artificial intelligence (AI) and machine learning (ML) techniques are revolutionizing several industrial and research fields like computer vision, autonomous driving, natural language processing, and speech recognition. These novel tools are already having a major impact in radiology, diagnostics…
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Value of machine learning in predicting TAVI outcomes
…specific patients. We aim to study the accuracy of various traditional machine learning (ML) algorithms in the prediction of TAVI outcomes. METHODS AND RESULTS: Clinical and laboratory data from 1,478 TAVI patients from a single centre were collected. The outcome measures were improvement of…
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Logistic Regression for Machine Learning in Process Tomography
The main goal of the research presented in this paper was to develop a refined machine learning algorithm for industrial tomography applications. The article presents algorithms based on logistic regression in relation to image reconstruction using electrical impedance tomography (EIT) and…
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Data on forecasting energy prices using machine learning
This article contains the data related to the research article “Long-term forecast of energy commodities price using machine learning” (Herrera et al., 2019). The datasets contain monthly prices of six main energy commodities covering a large period of nearly four decades. Four methods are applied…
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Transferable Machine-Learning Model of the Electron Density
…We introduce an atom-centered, symmetry-adapted framework to machine-learn the valence charge density based on a small number of reference calculations. The model is highly transferable, meaning it can be trained on electronic-structure data of small molecules and used to predict the charge density…
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Analysis of Trabecular Bone Mechanics Using Machine Learning
“Bone remodeling” is a dynamic process, and mutliphase analysis incorporated with the forecasting algorithm can help the biologists and orthopedics to interpret the laboratory generated results and to apply them in improving applications in the fields of “drug design, treatment, and therapy” of…
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Machine Learning SNP Based Prediction for Precision Medicine
…more accurate disease risk prediction models. Polygenic risk scoring and machine learning are two primary approaches for disease risk prediction. Despite recent improvements, the results of polygenic risk scoring remain limited due to the approaches that are currently used. By contrast, machine…
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Discovery of Novel Conotoxin Candidates Using Machine Learning
…To overcome these obstacles for discovery, we have created ConusPipe, a machine learning tool that utilizes prominent chemical characters of conotoxins to predict whether a certain transcript in a Conus transcriptome, which has no otherwise detectable homologs in current reference databases, is a…
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Wireless Fingerprinting Uncertainty Prediction Based on Machine Learning
…by given received signal strength (RSS) measurements through the use of machine learning (ML). Two ML methods are used, including an artificial neural network (ANN)-based approach and a Gaussian distribution (GD)-based method. The predicted location uncertainty is evaluated and further used to set…
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Application of machine learning in rheumatic disease research
Over the past decade, there has been a paradigm shift in how clinical data are collected, processed and utilized. Machine learning and artificial intelligence, fueled by breakthroughs in high-performance computing, data availability and algorithmic innovations, are paving the way to effective…
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