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Bayes Theorem

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Optimization of computational intelligence approach for the prediction of glutinous rice dehydration.

Journal of the science of food and agriculture
BACKGROUND: Five computational intelligence approaches, namely Gaussian process regression (GPR), artificial neural network (ANN), decision tree (DT), ensemble of trees (EoT) and support vector machine (SVM), were used to describe the evolution of mo...

Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy Restriction.

Journal of imaging informatics in medicine
Deep learning models have demonstrated great potential in medical imaging but are limited by the expensive, large volume of annotations required. To address this, we compared different active learning strategies by training models on subsets of the m...

Distribution-free Bayesian regularized learning framework for semi-supervised learning.

Neural networks : the official journal of the International Neural Network Society
In machine learning it is often necessary to assume or know the distribution of the data, however it is difficult to do so in practical applications. Aiming to this problem, this work, we propose a novel distribution-free Bayesian regularized learnin...

A machine learning approach to predict daptomycin exposure from two concentrations based on Monte Carlo simulations.

Antimicrobial agents and chemotherapy
Daptomycin is a concentration-dependent lipopeptide antibiotic for which exposure/effect relationships have been shown. Machine learning (ML) algorithms, developed to predict the individual exposure to drugs, have shown very good performances in comp...

Comparison of Machine Learning Algorithms for Heartbeat Detection Based on Accelerometric Signals Produced by a Smart Bed.

Sensors (Basel, Switzerland)
This work aims to compare the performance of Machine Learning (ML) and Deep Learning (DL) algorithms in detecting users' heartbeats on a smart bed. Targeting non-intrusive, continuous heart monitoring during sleep time, the smart bed is equipped with...

Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.

PloS one
The COVID-19 pandemic has had a significant impact on both the United Arab Emirates (UAE) and Malaysia, emphasizing the importance of developing accurate and reliable forecasting mechanisms to guide public health responses and policies. In this study...

Bayesian inference is facilitated by modular neural networks with different time scales.

PLoS computational biology
Various animals, including humans, have been suggested to perform Bayesian inferences to handle noisy, time-varying external information. In performing Bayesian inference by the brain, the prior distribution must be acquired and represented by sampli...

Reliable prediction of difficult airway for tracheal intubation from patient preoperative photographs by machine learning methods.

Computer methods and programs in biomedicine
BACKGROUND: Estimating the risk of a difficult tracheal intubation should help clinicians in better anaesthesia planning, to maximize patient safety. Routine bedside screenings suffer from low sensitivity.

A comparative evaluation of low-density lipoprotein cholesterol estimation: Machine learning algorithms versus various equations.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Given the critical importance of Low-density lipoprotein cholesterol (LDL-C) levels in determining cardiovascular risk, it is essential to measure LDL-C accurately. Since the Friedewald formula generates incorrect predictions in many circ...