AIMC Topic: Bayes Theorem

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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...
Machine Learning Republic of Korea Risk Factors Adolescent Suicidal Ideation Bayes Theorem Humans
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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...
Models, Neurological Bayes Theorem Memory, Short-Term Head Neural Networks, Computer Brain
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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...
Humans Neural Networks, Computer Electric Conductivity Uncertainty Bayes Theorem Electroencephalography
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Artificial Intelligence-Based Voice Assessment of Patients with Parkinson's Disease Off and On Treatment: Machine vs. Deep-Learning Comparison.

Sensors (Basel, Switzerland) Feb 18, 2023
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...
Parkinson Disease Bayes Theorem Levodopa Humans Artificial Intelligence Deep Learning
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Improving Intensive Care Unit Early Readmission Prediction Using Optimized and Explainable Machine Learning.

International journal of environmental research and public health Feb 16, 2023
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...
Patient Readmission Machine Learning Bayes Theorem Intensive Care Units Humans Artificial Intelligence
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Landslide susceptibility prediction improvements based on a semi-integrated supervised machine learning model.

Environmental science and pollution research international Feb 15, 2023
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...
Supervised Machine Learning Landslides Machine Learning Bayes Theorem Neural Networks, Computer
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Logistic regression technique is comparable to complex machine learning algorithms in predicting cognitive impairment related to post intensive care syndrome.

Scientific reports Feb 11, 2023
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...
Bayes Theorem Critical Care Algorithms Logistic Models Humans Machine Learning
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Comparative Studies on Resampling Techniques in Machine Learning and Deep Learning Models for Drug-Target Interaction Prediction.

Molecules (Basel, Switzerland) Feb 9, 2023
The prediction of drug-target interactions (DTIs) is a vital step in drug discovery. The success of machine learning and deep learning methods in accurately predicting DTIs plays a huge role in drug discovery. However, when dealing with learning algo...
Deep Learning Bayes Theorem Machine Learning Neural Networks, Computer Algorithms
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Fast and robust parameter estimation with uncertainty quantification for the cardiac function.

Computer methods and programs in biomedicine Feb 4, 2023
BACKGROUND AND OBJECTIVES: Parameter estimation and uncertainty quantification are crucial in computational cardiology, as they enable the construction of digital twins that faithfully replicate the behavior of physical patients. Many model parameter...
Bayes Theorem Heart Humans Neural Networks, Computer Ventricular Function Uncertainty
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Machine learning to improve frequent emergency department use prediction: a retrospective cohort study.

Scientific reports Feb 3, 2023
Frequent emergency department use is associated with many adverse events, such as increased risk for hospitalization and mortality. Frequent users have complex needs and associated factors are commonly evaluated using logistic regression. However, ot...
Machine Learning Retrospective Studies Adult Emergency Service, Hospital Chronic Disease Bayes Theorem Humans
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