359.866 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
Intelligent Machine Learning: Tailor-Making Macromolecules
…the amalgamation of the Kinetic Monte Carlo simulation approach and machine learning techniques. The former, an intelligent modeling tool, is able to model and visualize the intricate inter-relationships of polymerization recipes/conditions (as input variables) and microstructural features of the…
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Learned protein embeddings for machine learning
MOTIVATION: Machine-learning models trained on protein sequences and their measured functions can infer biological properties of unseen sequences without requiring an understanding of the underlying physical or biological mechanisms. Such models enable the prediction and discovery of sequences with…
Juga tersedia di: PubMed Central
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Transforming health policy through machine learning
In their Perspective, Ara Darzi and Hutan Ashrafian give us a tour of the future policymaker's machine learning toolkit.
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Machine Learning in Agriculture: A Review
Machine learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multi-disciplinary agri-technologies domain. In this paper, we present a comprehensive review of research dedicated to applications of machine…
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Quantum machine learning: a classical perspective
Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning (ML) techniques to impressive results in regression, classification, data generation and reinforcement learning tasks. Despite these successes, the proximity to the physical…
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Thalamocortical dysrhythmia detected by machine learning
…oscillations. We undertook a data-driven approach using support vector machine learning for analyzing resting-state electroencephalography oscillatory patterns in patients with Parkinson’s disease, neuropathic pain, tinnitus, and depression. We show a spectrally equivalent but spatially distinct…
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Machine Learning in Human Olfactory Research
…and data science, with its currently most popular implementation as machine learning, facilitate complex data-driven research approaches. The use of machine learning in human olfactory research included major approaches comprising 1) the study of the physiology of pattern-based odor detection and…
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Machine learning plastic deformation of crystals
…purely random or to some extent predictable. Here we show, by employing machine learning techniques such as regression neural networks and support vector machines that deformation predictability evolves with strain and crystal size. Using data from discrete dislocations dynamics simulations, the…
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Machine learning bandgaps of double perovskites
…impractical in high throughput studies, informatics-based statistical learning approaches can be a promising alternative. Here we demonstrate a systematic feature-engineering approach and a robust learning framework for efficient and accurate predictions of electronic bandgaps of double…
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Detecting Bacterial Vaginosis Using Machine Learning
Bacterial Vaginosis (BV) is the most common of vaginal infections diagnosed among women during the years where they can bear children. Yet, there is very little insight as to how it occurs. There are a vast number of criteria that can be taken into consideration to determine the presence of BV. The…
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A Developmental Approach to Machine Learning?
Visual learning depends on both the algorithms and the training material. This essay considers the natural statistics of infant- and toddler-egocentric vision. These natural training sets for human visual object recognition are very different from the training data fed into machine vision systems…
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Machine Learning Approaches in Cardiovascular Imaging
Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume of imaging data available for analyses. Machine…
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Enabling Machine Learning in Critical Care
Critical care units are home to some of the most sophisticated patient technology within hospitals. In parallel, the field of machine learning is advancing rapidly and increasingly touching our lives. To facilitate the adoption of machine learning approaches in critical care, we must become better…
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Machine Learning for Fetal Growth Prediction
…using the correct fetal weight standard, which was no different from the machine learning-based predicted standards, but higher than the regression-based predicted standards. Machine learning algorithms show promise in recovering missing fetal weight information.
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Classifying smoking urges via machine learning
BACKGROUND AND OBJECTIVE: Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning…
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Morphological Neuron Classification Using Machine Learning
…to classification and (ii) to assess and compare the accuracy of machine learning algorithms to classify neuron morphologies. The algorithms were trained on 430 digitally reconstructed neurons subjectively classified into layers and/or m-types using young and/or adult development state population…
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Machine Learning for Biomedical Literature Triage
This paper presents a machine learning system for supporting the first task of the biological literature manual curation process, called triage. We compare the performance of various classification models, by experimenting with dataset sampling factors and a set of features, as well as three…
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