AIMC Topic: Bayes Theorem

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An AI Approach for Identifying Patients With Cirrhosis.

Journal of clinical gastroenterology Jan 1, 2023
GOAL: The goal of this study was to evaluate an artificial intelligence approach, namely deep learning, on clinical text in electronic health records (EHRs) to identify patients with cirrhosis.
Neural Networks, Computer Artificial Intelligence Humans Liver Cirrhosis Bayes Theorem Machine Learning Algorithms
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Inferring turbulent environments via machine learning.

The European physical journal. E, Soft matter Dec 31, 2022
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...
Machine Learning Neural Networks, Computer Bayes Theorem
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High throughput optimization of medium composition for Escherichia coli protein expression using deep learning and Bayesian optimization.

Journal of bioscience and bioengineering Dec 29, 2022
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...
Bayes Theorem Escherichia coli Proteins Escherichia coli Green Fluorescent Proteins Deep Learning
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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 Data Mining Machine Learning Algorithms Random Forest Support Vector Machine
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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 ...
Bayes Theorem Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Artificial Intelligence Algorithms Neural Networks, Computer Imagination
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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 ...
Machine Learning Survival Rate Humans Bayes Theorem Neural Networks, Computer Lung Transplantation
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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...
Electronic Health Records Lung Neoplasms Humans Artificial Intelligence Bayes Theorem East Asian People
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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...
Neural Networks, Computer Sleep Stages Algorithms Humans Bayes Theorem Sleep
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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...
Bayes Theorem Time Algorithms Computer Simulation Neural Networks, Computer
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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 ...
Bayes Theorem Fires Fuzzy Logic Risk Factors Risk Assessment
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