AIMC Topic: Bayes Theorem

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Data-Driven Low-Frequency Oscillation Event Detection Strategy for Railway Electrification Networks.

Sensors (Basel, Switzerland) Dec 26, 2022
Low-frequency oscillations (LFO) occur in railway electrification systems due to the incorporation of new trains with switching converters. As a result, the increased harmonic content can cause catenary stability problems under certain conditions. Mo...
Bayes Theorem Algorithms Support Vector Machine Random Forest Data Mining Machine Learning
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Hybrid fuzzy deep neural network toward temporal-spatial-frequency features learning of motor imagery signals.

Scientific reports Dec 25, 2022
Achieving an efficient and reliable method is essential to interpret a user's brain wave and deliver an accurate response in biomedical signal processing. However, EEG patterns exhibit high variability across time and uncertainty due to noise and it ...
Imagination Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms Electroencephalography Artificial Intelligence Brain-Computer Interfaces Bayes Theorem
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Machine learning-based techniques to improve lung transplantation outcomes and complications: a systematic review.

BMC medical research methodology Dec 23, 2022
BACKGROUND: Machine learning has been used to develop predictive models to support clinicians in making better and more reliable decisions. The high volume of collected data in the lung transplant process makes it possible to extract hidden patterns ...
Survival Rate Machine Learning Lung Transplantation Bayes Theorem Humans Neural Networks, Computer
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Developing Artificial Intelligence Models for Extracting Oncologic Outcomes from Japanese Electronic Health Records.

Advances in therapy Dec 22, 2022
INTRODUCTION: A framework that extracts oncological outcomes from large-scale databases using artificial intelligence (AI) is not well established. Thus, we aimed to develop AI models to extract outcomes in patients with lung cancer using unstructure...
Humans Artificial Intelligence East Asian People Bayes Theorem Lung Neoplasms Electronic Health Records
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Classification at the accuracy limit: facing the problem of data ambiguity.

Scientific reports Dec 21, 2022
Data classification, the process of analyzing data and organizing it into categories or clusters, is a fundamental computing task of natural and artificial information processing systems. Both supervised classification and unsupervised clustering wor...
Sleep Bayes Theorem Humans Neural Networks, Computer Sleep Stages Algorithms
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Intelligent Sensors for dc Fault Location Scheme Based on Optimized Intelligent Architecture for HVdc Systems.

Sensors (Basel, Switzerland) Dec 16, 2022
We develop a probabilistic model for determining the location of dc-link faults in MT-HVdc networks using discrete wavelet transforms (DWTs), Bayesian optimization, and multilayer artificial neural networks (ANNs) based on local information. Likewise...
Time Bayes Theorem Algorithms Neural Networks, Computer Computer Simulation
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An Integrated Quantitative Risk Assessment Method for Underground Engineering Fires.

International journal of environmental research and public health Dec 16, 2022
Fires are one of the main disasters in underground engineering. In order to comprehensively describe and evaluate the risk of underground engineering fires, this study proposes a UEF risk assessment method based on EPB-FBN. Firstly, based on the EPB ...
Fires Risk Assessment Bayes Theorem Fuzzy Logic Risk Factors
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Detection of factors affecting kidney function using machine learning methods.

Scientific reports Dec 16, 2022
Due to the increasing prevalence of chronic kidney disease and its high mortality rate, study of risk factors affecting the progression of the disease is of great importance. Here in this work, we aim to develop a framework for using machine learning...
Risk Factors Kidney Machine Learning Bayes Theorem Humans
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Sparse inference and active learning of stochastic differential equations from data.

Scientific reports Dec 15, 2022
Automatic machine learning of empirical models from experimental data has recently become possible as a result of increased availability of computational power and dedicated algorithms. Despite the successes of non-parametric inference and neural-net...
Algorithms Bayes Theorem Neural Networks, Computer
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Structure and Base Analysis of Receptive Field Neural Networks in a Character Recognition Task.

Sensors (Basel, Switzerland) Dec 12, 2022
This paper explores extensions and restrictions of shallow convolutional neural networks with fixed kernels trained with a limited number of training samples. We extend the work recently done in research on Receptive Field Neural Networks (RFNN) and ...
Bayes Theorem Seeds Reproducibility of Results Neural Networks, Computer
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