AIMC Topic: Bayes Theorem

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The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Scientific reports Mar 13, 2023
Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increased significantly throughout the world. These hazardous wastes play an important role in environmental...
COVID-19 Deep Learning Humans Pandemics Environmental Pollution Bayes Theorem Plastics
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Toward explainable AI-empowered cognitive health assessment.

Frontiers in public health Mar 9, 2023
Explainable artificial intelligence (XAI) is of paramount importance to various domains, including healthcare, fitness, skill assessment, and personal assistants, to understand and explain the decision-making process of the artificial intelligence (A...
Dementia Bayes Theorem Awareness Neural Networks, Computer Artificial Intelligence Humans
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The utility of machine learning for predicting donor discard in abdominal transplantation.

Clinical transplantation Mar 8, 2023
BACKGROUND: Increasing access and better allocation of organs in the field of transplantation is a critical problem in clinical care. Limitations exist in accurately predicting allograft discard. Potential exists for machine learning to provide a bal...
Humans Logistic Models Bayes Theorem Machine Learning Tissue Donors
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Bayesian Statistics for Medical Devices: Progress Since 2010.

Therapeutic innovation & regulatory science Mar 3, 2023
The use of Bayesian statistics to support regulatory evaluation of medical devices began in the late 1990s. We review the literature, focusing on recent developments of Bayesian methods, including hierarchical modeling of studies and subgroups, borro...
United States Food and Drug Administration Sample Size Bayes Theorem Humans Child Artificial Intelligence United States Research Design
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A review of biowaste remediation and valorization for environmental sustainability: Artificial intelligence approach.

Environmental pollution (Barking, Essex : 1987) Feb 28, 2023
Biowaste remediation and valorization for environmental sustainability focuses on prevention rather than cleanup of waste generation by applying the fundamental recovery concept through biowaste-to-bioenergy conversion systems - an appropriate approa...
Neural Networks, Computer Agriculture Bayes Theorem Artificial Intelligence Biomass
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Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques.

Medical & biological engineering & computing Feb 27, 2023
The study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and reduce unnecessary oral glucose tolerance test (OGTT) applications for pregnant women who are not in the GD risk group using deep learning algorithms...
Female Deep Learning Prospective Studies Bayes Theorem Humans Pregnancy Diabetes, Gestational Machine Learning
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Visual recognition and prediction analysis of China's real estate index and stock trend based on CNN-LSTM algorithm optimized by neural networks.

PloS one Feb 24, 2023
Today, with the rapid growth of Internet technology, the changing trend of real estate finance has brought great an impact on the progress of the social economy. In order to explore the visual identification (VI) effect of Convolutional Neural Networ...
Bayes Theorem Neural Networks, Computer Algorithms China
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Predictors of suicide ideation among South Korean adolescents: A machine learning approach.

Journal of affective disorders Feb 23, 2023
BACKGROUND: The current study developed a predictive model for suicide ideation among South Korean (Korean) adolescents using a comprehensive set of factors across demographic, physical and mental health, academic, social, and behavioral domains. The...
Adolescent Bayes Theorem Republic of Korea Humans Suicidal Ideation Risk Factors Machine Learning
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Bayesian inference in ring attractor networks.

Proceedings of the National Academy of Sciences of the United States of America Feb 22, 2023
Working memories are thought to be held in attractor networks in the brain. These attractors should keep track of the uncertainty associated with each memory, so as to weigh it properly against conflicting new evidence. However, conventional attracto...
Memory, Short-Term Head Models, Neurological Bayes Theorem Brain Neural Networks, Computer
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Neural stochastic differential equations network as uncertainty quantification method for EEG source localization.

Biomedical physics & engineering express Feb 22, 2023
EEG source localization remains a challenging problem given the uncertain conductivity values of the volume conductor models (VCMs). As uncertain conductivities vary across people, they may considerably impact the forward and inverse solutions of the...
Electric Conductivity Uncertainty Bayes Theorem Electroencephalography Humans Neural Networks, Computer
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