359.866 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
Machine Learning in Modeling of Mouse Behavior
Mouse behavior is a primary outcome in evaluations of therapeutic efficacy. Exhaustive, continuous, multiparametric behavioral phenotyping is a valuable tool for understanding the pathophysiological status of mouse brain diseases. Automated home cage behavior analysis produces highly granulated…
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Machine learning models and over-fitting considerations
Machine learning models may outperform traditional statistical regression algorithms for predicting clinical outcomes. Proper validation of building such models and tuning their underlying algorithms is necessary to avoid over-fitting and poor generalizability, which smaller datasets can be more…
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Artificial intelligence and machine learning in nephropathology
…convolutional neural networks, that are currently the state of the art in machine learning software for this task. Because AI applications in nephropathology are still in their infancy, we show the power and potential of AI applications mostly in the example of oncopathology. Moreover, we discuss…
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Inverse Design of Materials by Machine Learning
…With the development of physics, statistics, computer science, etc., machine learning offers the opportunity to systematically find new materials. Especially by inverse design based on machine learning, one can make use of the existing knowledge without attempting mathematical inversion of the…
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Research Progress of Gliomas in Machine Learning
…of biomedical publications has led to the advent of the big-data era. Machine learning methods were applied as possible approaches to speed up the data mining processes. In this article, we reviewed the present situation and future orientations of machine learning application in gliomas within the…
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Machine learning for DCO-OFDM based LiFi
…appropriate DC bias level for DCO-OFDM is important. This paper applies machine learning (ML) algorithms to find optimum DC-bias value for DCO-OFDM based LiFi systems. For this, a dataset is generated for DCO-OFDM using MATLAB tool. Next, ML algorithms are applied using Python programming language…
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Enterprise Risk Assessment Based on Machine Learning
Scientific risk assessment is an important guarantee for the healthy development of an enterprise. With the continuous development and maturity of machine learning technology, it has played an important role in the field of data prediction and risk assessment. This paper conducts research on the…
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Predicting bloodstream infection outcome using machine learning
…patient stratification. We developed electronic medical record-based machine learning models that predict patient outcomes of BSI. The area under the receiver-operating characteristics curve was 0.82 for a full featured inclusive model, and 0.81 for a compact model using only 25 features. Our…
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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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