AIMC Topic: Bayes Theorem

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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...
Artificial Intelligence Deep Learning Parkinson Disease Bayes Theorem Humans Levodopa
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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...
Bayes Theorem Patient Readmission Machine Learning Intensive Care Units Artificial Intelligence Humans
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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 Bayes Theorem Neural Networks, Computer Machine Learning
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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...
Algorithms Logistic Models Humans Machine Learning Critical Care Bayes Theorem
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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...
Algorithms Bayes Theorem Neural Networks, Computer Deep Learning Machine Learning
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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...
Ventricular Function Neural Networks, Computer Heart Humans Bayes Theorem 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 Humans Emergency Service, Hospital Bayes Theorem Adult Chronic Disease
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Bayesian reconstruction of memories stored in neural networks from their connectivity.

PLoS computational biology Jan 30, 2023
The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stor...
Models, Neurological Neural Networks, Computer Neurons Bayes Theorem Algorithms
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Applications of Bayesian Neural Networks in Outlier Detection.

Big data Jan 27, 2023
Anomaly detection is crucial in a variety of domains, such as fraud detection, disease diagnosis, and equipment defect detection. With the development of deep learning, anomaly detection with Bayesian neural networks (BNNs) becomes a novel research t...
Fraud Deep Learning Bayes Theorem Spatial Analysis Neural Networks, Computer
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AccNet24: A deep learning framework for classifying 24-hour activity behaviours from wrist-worn accelerometer data under free-living environments.

International journal of medical informatics Jan 25, 2023
OBJECTIVE: Although machine learning techniques have been repeatedly used for activity prediction from wearable devices, accurate classification of 24-hour activity behaviour categories from accelerometry data remains a challenge. We developed and va...
Exercise Accelerometry Bayes Theorem Humans Deep Learning Wrist
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