AIMC Topic: Bayes Theorem

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Correspondence-based Generative Bayesian Deep Learning for semi-supervised volumetric medical image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 6, 2024
Automated medical image segmentation plays a crucial role in diverse clinical applications. The high annotation costs of fully-supervised medical segmentation methods have spurred a growing interest in semi-supervised methods. Existing semi-supervise...
Entropy Uncertainty Deep Learning Bayes Theorem Humans
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Automatic Prediction of Band Gaps of Inorganic Materials Using a Gradient Boosted and Statistical Feature Selection Workflow.

Journal of chemical information and modeling Feb 6, 2024
Machine learning (ML) methods can train a model to predict material properties by exploiting patterns in materials databases that arise from structure-property relationships. However, the importance of ML-based feature analysis and selection is often...
Databases, Factual Bayes Theorem Algorithms Workflow Machine Learning
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NPB-REC: A non-parametric Bayesian deep-learning approach for undersampled MRI reconstruction with uncertainty estimation.

Artificial intelligence in medicine Feb 5, 2024
The ability to reconstruct high-quality images from undersampled MRI data is vital in improving MRI temporal resolution and reducing acquisition times. Deep learning methods have been proposed for this task, but the lack of verified methods to quanti...
Magnetic Resonance Imaging Image Processing, Computer-Assisted Uncertainty Bayes Theorem Brain Deep Learning
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Explainable deep-neural-network supported scheme for tuberculosis detection from chest radiographs.

BMC medical imaging Feb 5, 2024
Chest radiographs are examined in typical clinical settings by competent physicians for tuberculosis diagnosis. However, this procedure is time consuming and subjective. Due to the growing usage of machine learning techniques in applied sciences, res...
Machine Learning Mass Screening Humans Bayes Theorem Radiography Tuberculosis
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Artificial intelligence-based prediction model for the elemental occurrence form of tailings and mine wastes.

Environmental research Feb 2, 2024
With the advent of the second industrial revolution, mining and metallurgical processes generate large volumes of tailings and mine wastes (TMW), which worsens global environmental pollution. Studying the occurrence of metal and metalloid elements in...
Mining Industrial Waste Metals Artificial Intelligence Environmental Monitoring Bayes Theorem
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Bayesian hypernetwork collaborates with time-difference evolutional network for temporal knowledge prediction.

Neural networks : the official journal of the International Neural Network Society Feb 1, 2024
A Temporal Knowledge Graph (TKG) is a sequence of Knowledge Graphs (KGs) attached with time information, in which each KG contains the facts that co-occur at the same timestamp. Temporal knowledge prediction (TKP) aims to predict future events given ...
Time Factors Algorithms Knowledge Bayes Theorem Humans Neural Networks, Computer Uncertainty
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Optimization of medium components for protein production by Escherichia coli with a high-throughput pipeline that uses a deep neural network.

Journal of bioscience and bioengineering Feb 1, 2024
To optimize rapidly the medium for green fluorescent protein expression by Escherichia coli with an introduced plasmid, pRSET/emGFP, a single-cycle optimization pipeline was applied. The pipeline included a deep neural network (DNN) and mathematical ...
Neural Networks, Computer Bayes Theorem Green Fluorescent Proteins Escherichia coli Algorithms
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An artificial intelligence approach to predicting personality types in dogs.

Scientific reports Jan 29, 2024
Canine personality and behavioural characteristics have a significant influence on relationships between domestic dogs and humans as well as determining the suitability of dogs for specific working roles. As a result, many researchers have attempted ...
Artificial Intelligence Machine Learning Dogs Humans Personality Bayes Theorem Animals Algorithms
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A quantum-based oversampling method for classification of highly imbalanced and overlapped data.

Experimental biology and medicine (Maywood, N.J.) Jan 28, 2024
Data imbalance is a challenging problem in classification tasks, and when combined with class overlapping, it further deteriorates classification performance. However, existing studies have rarely addressed both issues simultaneously. In this article...
Support Vector Machine Bayes Theorem Algorithms Cluster Analysis
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Data-driven approach to quantify trust in medical devices using Bayesian networks.

Experimental biology and medicine (Maywood, N.J.) Jan 27, 2024
Bayesian networks are increasingly used to quantify the uncertainty of subjective and stochastic concepts such as trust. In this article, we propose a data-driven approach to estimate Bayesian parameters in the domain of wearable medical devices. Our...
Bayes Theorem Trust
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