AIMC Topic: Bayes Theorem

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EEG-Based Emotion Classification in Financial Trading Using Deep Learning: Effects of Risk Control Measures.

Sensors (Basel, Switzerland) Mar 26, 2023
Day traders in the financial markets are under constant pressure to make rapid decisions and limit capital losses in response to fluctuating market prices. As such, their emotional state can greatly influence their decision-making, leading to subopti...
Electroencephalography Emotions Fear Bayes Theorem Deep Learning
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High-Level CNN and Machine Learning Methods for Speaker Recognition.

Sensors (Basel, Switzerland) Mar 25, 2023
Speaker Recognition (SR) is a common task in AI-based sound analysis, involving structurally different methodologies such as Deep Learning or "traditional" Machine Learning (ML). In this paper, we compared and explored the two methodologies on the DE...
Acoustics Sound Machine Learning Bayes Theorem
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Accuracies of various types of spinal robot in robot-assisted pedicle screw insertion: a Bayesian network meta-analysis.

Journal of orthopaedic surgery and research Mar 25, 2023
BACKGROUND: With the popularization of robot-assisted spinal surgeries, it is still uncertain whether robots with different designs could lead to different results in the accuracy of pedicle screw placement. This study aimed to compare the pedicle sc...
Retrospective Studies Robotics Pedicle Screws Bayes Theorem Lumbar Vertebrae Spinal Fusion Surgery, Computer-Assisted
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Development of a patients' satisfaction analysis system using machine learning and lexicon-based methods.

BMC health services research Mar 23, 2023
BACKGROUND: Patients' rights are integral to medical ethics. This study aimed to perform sentiment analysis and opinion mining on patients' messages by a combination of lexicon-based and machine learning methods to identify positive or negative comme...
Patient Satisfaction ROC Curve Bayes Theorem Humans Artificial Intelligence Machine Learning
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Application of a developed triple-classification machine learning model for carcinogenic prediction of hazardous organic chemicals to the US, EU, and WHO based on Chinese database.

Ecotoxicology and environmental safety Mar 20, 2023
Cancer, the second largest human disease, has become a major public health problem. The prediction of chemicals' carcinogenicity before their synthesis is crucial. In this paper, seven machine learning algorithms (i.e., Random Forest (RF), Logistic R...
Carcinogenesis Bayes Theorem United States Support Vector Machine Carcinogens European Union World Health Organization Hazardous Substances Algorithms Machine Learning Databases, Factual China Organic Chemicals
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Identifying Disease of Interest With Deep Learning Using Diagnosis Code.

Journal of Korean medical science Mar 20, 2023
BACKGROUND: Autoencoder (AE) is one of the deep learning techniques that uses an artificial neural network to reconstruct its input data in the output layer. We constructed a novel supervised AE model and tested its performance in the prediction of a...
Bayes Theorem Male Deep Learning Humans Neural Networks, Computer
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Confused or not: decoding brain activity and recognizing confusion in reasoning learning using EEG.

Journal of neural engineering Mar 17, 2023
Confusion is the primary epistemic emotion in the learning process, influencing students' engagement and whether they become frustrated or bored. However, research on confusion in learning is still in its early stages, and there is a need to better u...
Humans Neural Networks, Computer Bayes Theorem Brain Electroencephalography Emotions
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Modelling daily plant growth response to environmental conditions in Chinese solar greenhouse using Bayesian neural network.

Scientific reports Mar 16, 2023
Understanding how plants respond to environmental conditions such as temperature, CO, humidity, and light radiation is essential for plant growth. This paper proposes an Artificial Neural Network (ANN) model to predict plant response to environmental...
Sunlight Neural Networks, Computer Plant Development Temperature Bayes Theorem
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Machine learning models trained on synthetic datasets of multiple sample sizes for the use of predicting blood pressure from clinical data in a national dataset.

PloS one Mar 16, 2023
INTRODUCTION: The potential for synthetic data to act as a replacement for real data in research has attracted attention in recent months due to the prospect of increasing access to data and overcoming data privacy concerns when sharing data. The fie...
Blood Pressure Sample Size Humans Artificial Intelligence Bayes Theorem Machine Learning
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Machine Learning Hybrid Model for the Prediction of Chronic Kidney Disease.

Computational intelligence and neuroscience Mar 14, 2023
To diagnose an illness in healthcare, doctors typically conduct physical exams and review the patient's medical history, followed by diagnostic tests and procedures to determine the underlying cause of symptoms. Chronic kidney disease (CKD) is curren...
Support Vector Machine Bayes Theorem Random Forest Machine Learning Humans Algorithms Neural Networks, Computer
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