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Bayes Theorem

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Authentication of beef cuts by multielement and machine learning approaches.

Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS)
BACKGROUND: Brazil has consolidated a relevant position in the world market, being the largest exporter and second producer of beef. Genetics, feeding system, geographic origin and climate influence the multielement profile of beef. The feasibility o...

The usefulness of artificial intelligence for safety assessment of different transport modes.

Accident; analysis and prevention
Recent research in transport safety focuses on the processing of large amounts of available data by means of intelligent systems, in order to decrease the number of accidents for transportation users. Several Machine Learning (ML) and Artificial Inte...

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

Sensors (Basel, Switzerland)
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...

High-Level CNN and Machine Learning Methods for Speaker Recognition.

Sensors (Basel, Switzerland)
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...

Accuracies of various types of spinal robot in robot-assisted pedicle screw insertion: a Bayesian network meta-analysis.

Journal of orthopaedic surgery and research
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...

Development of a patients' satisfaction analysis system using machine learning and lexicon-based methods.

BMC health services research
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...

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
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...

Identifying Disease of Interest With Deep Learning Using Diagnosis Code.

Journal of Korean medical science
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...

Confused or not: decoding brain activity and recognizing confusion in reasoning learning using EEG.

Journal of neural engineering
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...

Modelling daily plant growth response to environmental conditions in Chinese solar greenhouse using Bayesian neural network.

Scientific reports
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...