214,423 results for machine learning
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Detecting phishing websites using machine learning technique
…In this study, the author proposed a URL detection technique based on machine learning approaches. A recurrent neural network method is employed to detect phishing URL. Researcher evaluated the proposed method with 7900 malicious and 5800 legitimate sites, respectively. The experiments’ outcome…
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Medicolite-Machine Learning-Based Patient Care Model
This paper discusses the machine learning effect on healthcare and the development of an application named “Medicolite” in which various modules have been developed for convenience with health-related problems like issues with diet. It also provides online doctor appointments from home and…
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Predicting anesthetic infusion events using machine learning
Recently, research has been conducted to automatically control anesthesia using machine learning, with the aim of alleviating the shortage of anesthesiologists. In this study, we address the problem of predicting decisions made by anesthesiologists during surgery using machine learning…
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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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Emulating complex simulations by machine learning methods
BACKGROUND: The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More specifically, the simulator is a patient-specific model that integrates metabolic, nutritional, and lifestyle data to predict the metabolic and…
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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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Machine learning discovery of high-temperature polymers
To formulate a machine learning (ML) model to establish the polymer's structure-property correlation for glass transition temperature [Formula: see text] , we collect a diverse set of nearly 13,000 real homopolymers from the largest polymer database, PoLyInfo. We train the deep neural network (DNN)…
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Machine-learning a virus assembly fitness landscape
…a fitness landscape in terms of the assembly efficiency. Using latest machine-learning techniques by establishing a neural network, we show that the intensive computation can be short-circuited in a matter of minutes to astounding accuracy.
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Identifying epilepsy psychiatric comorbidities with machine learning
OBJECTIVE: People with epilepsy are at increased risk for mental health comorbidities. Machine-learning methods based on spoken language can detect suicidality in adults. This study’s purpose was to use spoken words to create machine-learning classifiers that identify current or lifetime history of…
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Mycobacterium abscessus Drug Discovery using Machine Learning
…M. abscessus infections. Our approach to drug discovery integrates machine learning, medicinal chemistry and in vitro testing and has been previously applied to Mycobacterium tuberculosis. We have now identified several novel 1-(phenylsulfonyl)-1H-benzimidazol-2-amines that have weak activity on M…
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Perspectives in machine learning for wildlife conservation
…can capitalize on large datasets generated by modern sensors by combining machine learning approaches with domain knowledge. Incorporating machine learning into ecological workflows could improve inputs for ecological models and lead to integrated hybrid modeling tools. This approach will require…
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Machine learning toward high-performance electrochemical sensors
The so-coined fourth paradigm in science has reached the sensing area, with the use of machine learning (ML) toward data-driven improvements in sensitivity, reproducibility, and accuracy, along with the determination of multiple targets from a single measurement using multi-output regression…
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Machine Learning Assisted Clustering of Nanoparticle Structures
[Image: see text] We propose a scheme for the automatic separation (i.e., clustering) of data sets composed of several nanoparticle (NP) structures by means of Machine Learning techniques. These data sets originate from atomistic simulations, such as global optimizations searches and molecular…
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Human Gait Activity Recognition Machine Learning Methods
…different gait activities within each gait recording by utilizing Machine Learning algorithms. In line with this, various Machine Learning methods were tested and compared to establish the best-performing algorithm for the classification of the recorded gait information. The combination of…
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Inferred networks, machine learning, and health data
This paper presents a network science approach to investigate a health information dataset, the Sexual Acquisition and Transmission of HIV Cooperative Agreement Program (SATHCAP), to uncover hidden relationships that can be used to suggest targeted health interventions. From the data, four key…
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Automatic detection of pain using machine learning
…non-invasive, objective pain measurements through biosensors coupled with machine learning algorithms. In the current study, a physiological dataset associated with acute pain induction in healthy adults was leveraged to develop an algorithm capable of detecting pain in real-time and in natural…
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Machine-Learning Classification of Pulse Waveform Quality
…The present study aimed to determine the effectiveness of using machine-learning analysis in discriminating between high-quality and low-quality pulse waveforms induced by applying different contact pressures. Radial blood pressure waveform (BPW) signals were measured noninvasively in healthy young…
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