AIMC Topic: Bayes Theorem

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Predicting Conserved Water Molecules in Binding Sites of Proteins Using Machine Learning Methods and Combining Features.

Computational and mathematical methods in medicine Oct 3, 2022
Water molecules play an important role in many biological processes in terms of stabilizing protein structures, assisting protein folding, and improving binding affinity. It is well known that, due to the impacts of various environmental factors, it ...
Binding Sites Solvents Humans Proteins Water Machine Learning Bayes Theorem Support Vector Machine
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Automatic Evolution of Machine-Learning-Based Quantum Dynamics with Uncertainty Analysis.

Journal of chemical theory and computation Oct 2, 2022
The machine learning approaches are applied in the dynamical simulation of open quantum systems. The long short-term memory recurrent neural network (LSTM-RNN) models are used to simulate the long-time quantum dynamics, which are built based on the k...
Bayes Theorem Neural Networks, Computer Uncertainty Machine Learning
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Uncertainty Estimation Using Variational Mixture of Gaussians Capsule Network for Health Image Classification.

Computational intelligence and neuroscience Sep 30, 2022
Capsule Networks have shown great promise in image recognition due to their ability to recognize the pose, texture, and deformation of objects and object parts. However, the majority of the existing capsule networks are deterministic with limited abi...
Reproducibility of Results Bayes Theorem Normal Distribution Uncertainty Neural Networks, Computer
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Early Prediction of Diabetes Using an Ensemble of Machine Learning Models.

International journal of environmental research and public health Sep 28, 2022
Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of significant complications, including cardiovascular disease, kidney failure, diabetic retinopathy, and neuropathy, among others, which contribute to an incr...
Analysis of Variance Machine Learning Diabetes Mellitus Area Under Curve Bayes Theorem Humans
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Multinomial Naive Bayesian Classifier Framework for Systematic Analysis of Smart IoT Devices.

Sensors (Basel, Switzerland) Sep 27, 2022
Businesses need to use sentiment analysis, powered by artificial intelligence and machine learning to forecast accurately whether or not consumers are satisfied with their offerings. This paper uses a deep learning model to analyze thousands of revie...
Systems Analysis Bayes Theorem Attitude Artificial Intelligence Machine Learning
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Human reliability analysis in deep excavation projects using a fuzzy Bayesian HEART-5M integrated method: case of a residential tower in north Tehran.

International journal of occupational safety and ergonomics : JOSE Sep 26, 2022
Numerous labourers lose their lives or suffer from injuries and disabilities yearly due to the lack of safety enforcement in construction projects and accidents caused by excavation collapses. The identification and ranking of human errors have alwa...
Iran Probability Humans Fuzzy Logic Reproducibility of Results Bayes Theorem
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Assessing spatial connectivity effects on daily streamflow forecasting using Bayesian-based graph neural network.

The Science of the total environment Sep 23, 2022
Data-driven models have been widely developed and achieved impressive results in streamflow prediction. However, the existing data-driven models mostly focus on the selection of input features and the adjustment of model structure, and less on the im...
Forecasting Reproducibility of Results Neural Networks, Computer Hydrology Bayes Theorem Rivers
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Graph-based representation for identifying individual travel activities with spatiotemporal trajectories and POI data.

Scientific reports Sep 21, 2022
Individual daily travel activities (e.g., work, eating) are identified with various machine learning models (e.g., Bayesian Network, Random Forest) for understanding people's frequent travel purposes. However, labor-intensive engineering work is ofte...
Humans Bayes Theorem Machine Learning Travel Neural Networks, Computer Algorithms
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A Novel Supervised Filter Feature Selection Method Based on Gaussian Probability Density for Fault Diagnosis of Permanent Magnet DC Motors.

Sensors (Basel, Switzerland) Sep 20, 2022
For permanent magnet DC motors (PMDCMs), the amplitude of the current signals gradually decreases after the motor starts. In this work, the time domain features and time-frequency-domain features extracted from several successive segments of current ...
Normal Distribution Magnets Algorithms Support Vector Machine Bayes Theorem
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Implementation of Machine Learning Mechanism for Recognising Prostate Cancer through Photoacoustic Signal.

Contrast media & molecular imaging Sep 20, 2022
Biological tissues may be studied using photoacoustic (PA) spectroscopy, which can yield a wealth of physical and chemical data. However, it is really challenging to directly analyse these tissues because of a lot of data. Data mining techniques can ...
Spectrum Analysis Male Machine Learning Bayes Theorem Humans Algorithms Lipids Prostatic Neoplasms
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