113.116 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
Machine Learning: A Crucial Tool for Sensor Design
…and other related fields. As a key tool for sensor data analysis, machine learning is becoming a core part of novel sensor design. Dividing a complete machine learning process into three steps: data pre-treatment, feature extraction and dimension reduction, and system modeling, this paper provides…
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Machine Learning Methods for Prediction of CDK-Inhibitors
…similarity search methods. In this work we have evaluated and developed machine learning methods for identification of CDKIs. We used different compositional features and evolutionary information in the form of PSSMs, from CDKIs and non-CDKIs for generating SVM and ANN classifiers. In the first…
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Image-based crystal detection: a machine-learning approach
…on the likelihood of containing crystalline material as perceived by a machine-learning algorithm. The system can be incorporated into existing crystallization-analysis pipelines, whereby specialists examine images as they normally would with the exception that the images appear in rank order…
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A Protein Classification Benchmark collection for machine learning
Protein classification by machine learning algorithms is now widely used in structural and functional annotation of proteins. The Protein Classification Benchmark collection () was created in order to provide standard datasets on which the performance of machine learning methods can be compared. It…
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APPLYING MACHINE LEARNING TECHNIQUES IN DETECTING BACTERIAL VAGINOSIS
There are several diseases which arise because of changes in the microbial communities in the body. Scientists continue to conduct research in a quest to find the catalysts that provoke these changes in the naturally occurring microbiota. Bacterial Vaginosis (BV) is a disease that fits the above…
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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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Artikel Jurnal Teks lengkap
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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