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Bayes Theorem

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Inferring turbulent environments via machine learning.

The European physical journal. E, Soft matter
The problem of classifying turbulent environments from partial observation is key for some theoretical and applied fields, from engineering to earth observation and astrophysics, e.g., to precondition searching of optimal control policies in differen...

High throughput optimization of medium composition for Escherichia coli protein expression using deep learning and Bayesian optimization.

Journal of bioscience and bioengineering
To improve synthetic media for protein expression in Escherichia coli, a strategy using deep neural networks (DNN) and Bayesian optimization was performed in this study. To obtain training data for a deep learning algorithm, E. coli harvesting a plas...

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

Sensors (Basel, Switzerland)
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...

Hybrid fuzzy deep neural network toward temporal-spatial-frequency features learning of motor imagery signals.

Scientific reports
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 ...

Machine learning-based techniques to improve lung transplantation outcomes and complications: a systematic review.

BMC medical research methodology
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 ...

Developing Artificial Intelligence Models for Extracting Oncologic Outcomes from Japanese Electronic Health Records.

Advances in therapy
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...

Classification at the accuracy limit: facing the problem of data ambiguity.

Scientific reports
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...

Intelligent Sensors for dc Fault Location Scheme Based on Optimized Intelligent Architecture for HVdc Systems.

Sensors (Basel, Switzerland)
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...

An Integrated Quantitative Risk Assessment Method for Underground Engineering Fires.

International journal of environmental research and public health
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 ...

Detection of factors affecting kidney function using machine learning methods.

Scientific reports
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...