AIMC Topic: Bayes Theorem

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A review of biowaste remediation and valorization for environmental sustainability: Artificial intelligence approach.

Environmental pollution (Barking, Essex : 1987)
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...

Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques.

Medical & biological engineering & computing
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...

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
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...

Predictors of suicide ideation among South Korean adolescents: A machine learning approach.

Journal of affective disorders
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...

Bayesian inference in ring attractor networks.

Proceedings of the National Academy of Sciences of the United States of America
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...

Neural stochastic differential equations network as uncertainty quantification method for EEG source localization.

Biomedical physics & engineering express
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...

Artificial Intelligence-Based Voice Assessment of Patients with Parkinson's Disease Off and On Treatment: Machine vs. Deep-Learning Comparison.

Sensors (Basel, Switzerland)
Parkinson's Disease (PD) is one of the most common non-curable neurodegenerative diseases. Diagnosis is achieved clinically on the basis of different symptoms with considerable delays from the onset of neurodegenerative processes in the central nervo...

Improving Intensive Care Unit Early Readmission Prediction Using Optimized and Explainable Machine Learning.

International journal of environmental research and public health
It is of great interest to develop and introduce new techniques to automatically and efficiently analyze the enormous amount of data generated in today's hospitals, using state-of-the-art artificial intelligence methods. Patients readmitted to the IC...

Landslide susceptibility prediction improvements based on a semi-integrated supervised machine learning model.

Environmental science and pollution research international
Differences in model application effectiveness, insufficient numbers of disaster samples, and unreasonable selection of non-hazard samples are common problems in landslide susceptibility studies. Therefore, in this paper, we propose a semi-integrated...

Logistic regression technique is comparable to complex machine learning algorithms in predicting cognitive impairment related to post intensive care syndrome.

Scientific reports
To evaluate the performance of machine learning (ML) models and to compare it with logistic regression (LR) technique in predicting cognitive impairment related to post intensive care syndrome (PICS-CI). We conducted a prospective observational study...