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Bayes Theorem

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Large-scale spatiotemporal deep learning predicting urban residential indoor PM concentration.

Environment international
Indoor PM pollution is one of the leading causes of death and disease worldwide. As monitoring indoor PM concentrations on a large scale is challenging, it is urgent to assess population-level exposure and related health risks to develop an easy-to-u...

Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction.

IEEE transactions on bio-medical engineering
An Individual Survival Distribution (ISD) models a patient's personalized survival probability at all future time points. Previously, ISD models have been shown to produce accurate and personalized survival estimates (for example, time to relapse or ...

ENAS-B: Combining ENAS With Bayesian Optimization for Automatic Design of Optimal CNN Architectures for Breast Lesion Classification From Ultrasound Images.

Ultrasonic imaging
Efficient Neural Architecture Search (ENAS) is a recent development in searching for optimal cell structures for Convolutional Neural Network (CNN) design. It has been successfully used in various applications including ultrasound image classificatio...

Uncertainty-based Active Learning by Bayesian U-Net for Multi-label Cone-beam CT Segmentation.

Journal of endodontics
INTRODUCTION: Training of Artificial Intelligence (AI) for biomedical image analysis depends on large annotated datasets. This study assessed the efficacy of Active Learning (AL) strategies training AI models for accurate multilabel segmentation and ...

Development and performance comparison of optimized machine learning-based regression models for predicting energy-related carbon dioxide emissions.

Environmental science and pollution research international
Accurate prediction of CO emissions for the countries has become a crucial task in decision-making processes for planning energy conversion and usage, supporting the design of effective emissions reduction strategies, and helping to achieve the goal ...

Markov chain stochastic DCA and applications in deep learning with PDEs regularization.

Neural networks : the official journal of the International Neural Network Society
This paper addresses a large class of nonsmooth nonconvex stochastic DC (difference-of-convex functions) programs where endogenous uncertainty is involved and i.i.d. (independent and identically distributed) samples are not available. Instead, we ass...

A model-independent redundancy measure for human versus ChatGPT authorship discrimination using a Bayesian probabilistic approach.

Scientific reports
The academic and scientific world in general is increasingly concerned about their inability to determine and ascertain the identity of the writer of a text. More and more often the question arises as to whether a scientific article or work handed in...

Implementing link prediction in protein networks via feature fusion models based on graph neural networks.

Computational biology and chemistry
MOTIVATION: Protein-protein interactions serve as the cornerstone for various biochemical processes within biological organisms. Existing research methodologies predominantly employ link prediction techniques to analyze these interaction networks. Ho...

Identifying self-disclosed anxiety on Twitter: A natural language processing approach.

Psychiatry research
BACKGROUND: Text analyses of social media posts are a promising source of mental health information. This study used natural language processing to explore distinct language patterns on Twitter related to self-reported anxiety diagnosis.

Design and implementation of adolescent health Latin dance teaching system under artificial intelligence technology.

PloS one
Since various dance teaching systems have attracted much attention with the development of Artificial Intelligence (AI) technology, this paper improves the recognition performance of Latin dance teaching systems by optimizing the action recognition m...