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Bayes Theorem

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Machine learning validation of the AVAS classification compared to ultrasound mapping in a multicentre study.

Scientific reports
The Arteriovenous Access Stage (AVAS) classification simplifies information about suitability of vessels for vascular access (VA). It's been previously validated in a clinical study. Here, AVAS performance was tested against multiple ultrasound mappi...

Investigating the performance of multivariate LSTM models to predict the occurrence of Distributed Denial of Service (DDoS) attack.

PloS one
In the current cybersecurity landscape, Distributed Denial of Service (DDoS) attacks have become a prevalent form of cybercrime. These attacks are relatively easy to execute but can cause significant disruption and damage to targeted systems and netw...

AI contextual information shapes moral and aesthetic judgments of AI-generated visual art.

Cognition
Throughout history, art creation has been regarded as a uniquely human means to express original ideas, emotions, and experiences. However, as Generative Artificial Intelligence reshapes visual, aesthetic, legal, and economic culture, critical questi...

Robust estimation of skin physiological parameters from hyperspectral images using Bayesian neural networks.

Journal of biomedical optics
SIGNIFICANCE: Machine learning models for the direct extraction of tissue parameters from hyperspectral images have been extensively researched recently, as they represent a faster alternative to the well-known iterative methods such as inverse Monte...

A meta-learning imbalanced classification framework via boundary enhancement strategy with Bayes imbalance impact index.

Neural networks : the official journal of the International Neural Network Society
For imbalanced classification problem, algorithm-level methods can effectively avoid the information loss and noise introduction of data-level methods. However, the differences in the characteristics of the datasets, such as imbalance ratio, data dim...

Federated learning meets Bayesian neural network: Robust and uncertainty-aware distributed variational inference.

Neural networks : the official journal of the International Neural Network Society
Federated Learning (FL) is a popular framework for data privacy protection in distributed machine learning. However, current FL faces some several problems and challenges, including the limited amount of client data and data heterogeneity. These lead...

Application of functional near-infrared spectroscopy and machine learning to predict treatment response after six months in major depressive disorder.

Translational psychiatry
Depression treatment responses vary widely among individuals. Identifying objective biomarkers with predictive accuracy for therapeutic outcomes can enhance treatment efficiency and avoid ineffective therapies. This study investigates whether functio...

Elephant Sound Classification Using Deep Learning Optimization.

Sensors (Basel, Switzerland)
Elephant sound identification is crucial in wildlife conservation and ecological research. The identification of elephant vocalizations provides insights into the behavior, social dynamics, and emotional expressions, leading to elephant conservation....

Enhancing stroke disease classification through machine learning models via a novel voting system by feature selection techniques.

PloS one
Heart disease remains a leading cause of mortality and morbidity worldwide, necessitating the development of accurate and reliable predictive models to facilitate early detection and intervention. While state of the art work has focused on various ma...

Enhancing meteorological data reliability: An explainable deep learning method for anomaly detection.

Journal of environmental management
Accurate meteorological observation data is of great importance to human production activities. Meteorological observation systems have been advancing toward automation, intelligence, and informatization. Yet, instrumental malfunctions and unstable s...