AIMC Topic: Bayes Theorem

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Application of machine learning to the monitoring and prediction of food safety: A review.

Comprehensive reviews in food science and food safety Dec 14, 2021
Machine learning (ML) has proven to be a useful technology for data analysis and modeling in a wide variety of domains, including food science and engineering. The use of ML models for the monitoring and prediction of food safety is growing in recent...
Machine Learning Foodborne Diseases Humans Neural Networks, Computer Bayes Theorem Food Safety
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Hyperparameter Optimization for Transfer Learning of VGG16 for Disease Identification in Corn Leaves Using Bayesian Optimization.

Big data Dec 10, 2021
One of the world's most widely grown crops is corn. Crop loss due to diseases has a major economic effect, putting the food supply in jeopardy. In many parts of the world, lack of infrastructure still slows disease diagnosis. In this context, effecti...
Plant Leaves Bayes Theorem Zea mays Neural Networks, Computer Machine Learning
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Risk Prediction by Using Artificial Neural Network in Global Software Development.

Computational intelligence and neuroscience Dec 9, 2021
The demand for global software development is growing. The nonavailability of software experts at one place or a country is the reason for the increase in the scope of global software development. Software developers who are located in different part...
Algorithms Neural Networks, Computer Bayes Theorem Software
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A Comparative Performance Assessment of Optimized Multilevel Ensemble Learning Model with Existing Classifier Models.

Big data Dec 8, 2021
To predict the class level of any classification problem, predictive models are used and mostly a single predictive model is built to predict the class level of any classification problem; current research considers multiple predictive models to pred...
Animals Neural Networks, Computer Bayes Theorem Machine Learning Algorithms
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A study of uncertainties in groundwater vulnerability modelling using Bayesian model averaging (BMA).

Journal of environmental management Dec 8, 2021
Bayesian Model Averaging (BMA) is used to study inherent uncertainties using the Basic DRASTIC Framework (BDF) for assessing the groundwater vulnerability in a study area related to Lake Urmia. BMA is naturally an Inclusive Multiple Modelling (IMM) s...
Environmental Monitoring Bayes Theorem Uncertainty Artificial Intelligence Groundwater
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An Improved Brain MRI Classification Methodology Based on Statistical Features and Machine Learning Algorithms.

Computational and mathematical methods in medicine Dec 7, 2021
In this paper, we have proposed a novel methodology based on statistical features and different machine learning algorithms. The proposed model can be divided into three main stages, namely, preprocessing, feature extraction, and classification. In t...
Computational Biology Magnetic Resonance Imaging Brain Humans Brain Neoplasms Neural Networks, Computer Machine Learning Image Interpretation, Computer-Assisted Neuroimaging Algorithms Decision Trees Brain Diseases Bayes Theorem
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A Multilayer Perceptron Neural Network Model to Classify Hypertension in Adolescents Using Anthropometric Measurements: A Cross-Sectional Study in Sarawak, Malaysia.

Computational and mathematical methods in medicine Dec 7, 2021
This study outlines and developed a multilayer perceptron (MLP) neural network model for adolescent hypertension classification focusing on the use of simple anthropometric and sociodemographic data collected from a cross-sectional research study in ...
Cross-Sectional Studies Male Prevalence Adolescent Neural Networks, Computer Female Humans Sociodemographic Factors Anthropometry Malaysia Bayes Theorem Computational Biology Hypertension
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Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting.

Sensors (Basel, Switzerland) Nov 30, 2021
Data-driven forecasts of air quality have recently achieved more accurate short-term predictions. However, despite their success, most of the current data-driven solutions lack proper quantifications of model uncertainty that communicate how much to ...
Uncertainty Bayes Theorem Air Pollution Reproducibility of Results Deep Learning Forecasting
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Neural Architecture Search for 1D CNNs-Different Approaches Tests and Measurements.

Sensors (Basel, Switzerland) Nov 30, 2021
In the field of sensors, in areas such as industrial, clinical, or environment, it is common to find one dimensional (1D) formatted data (e.g., electrocardiogram, temperature, power consumption). A very promising technique for modelling this informat...
Electrocardiography Bayes Theorem Neural Networks, Computer
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Mental Stress Classification Based on a Support Vector Machine and Naive Bayes Using Electrocardiogram Signals.

Sensors (Basel, Switzerland) Nov 27, 2021
Examining mental health is crucial for preventing mental illnesses such as depression. This study presents a method for classifying electrocardiogram (ECG) data into four emotional states according to the stress levels using one-against-all and naive...
Support Vector Machine Bayes Theorem ROC Curve Electrocardiography Humans Algorithms
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