AI Medical Compendium Topic:
Bayes Theorem

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ESVM-SWRF: Ensemble SVM-based sample weighted random forests for liver disease classification.

International journal for numerical methods in biomedical engineering Sep 21, 2021
Recently, a significant way to diagnose the disease is using the model of medical data mining. The most challenging task in the healthcare field is to face a large amount of data during disease analyzes and prediction. Once the data are transformed i...
Humans Support Vector Machine Bayes Theorem Liver Diseases Neural Networks, Computer Algorithms
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Augmented sequence features and subcellular localization for functional characterization of unknown protein sequences.

Medical & biological engineering & computing Sep 20, 2021
Advances in high-throughput techniques lead to evolving a large number of unknown protein sequences (UPS). Functional characterization of UPS is significant for the investigation of disease symptoms and drug repositioning. Protein subcellular localiz...
Algorithms Support Vector Machine Neural Networks, Computer Amino Acid Sequence Proteins Bayes Theorem
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Forecasting Erroneous Neural Machine Translation of Disease Symptoms: Development of Bayesian Probabilistic Classifiers for Cross-Lingual Health Translation.

International journal of environmental research and public health Sep 19, 2021
BACKGROUND: Machine translation (MT) technologies have increasing applications in healthcare. Despite their convenience, cost-effectiveness, and constantly improved accuracy, research shows that the use of MT tools in medical or healthcare settings p...
Humans Translations Reproducibility of Results Machine Learning Bayes Theorem
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Multi-Class brain normality and abnormality diagnosis using modified Faster R-CNN.

International journal of medical informatics Sep 16, 2021
BACKGROUND AND OBJECTIVE: The detection and analysis of brain disorders through medical imaging techniques are extremely important to get treatment on time and sustain a healthy lifestyle. Disorders cause permanent brain damage and alleviate the life...
Bayes Theorem Neural Networks, Computer Artificial Intelligence Brain Support Vector Machine Humans
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Design of Biopharmaceutical Formulations Accelerated by Machine Learning.

Molecular pharmaceutics Sep 14, 2021
In addition to activity, successful biological drugs must exhibit a series of suitable developability properties, which depend on both protein sequence and buffer composition. In the context of this high-dimensional optimization problem, advanced alg...
Humans Machine Learning Nanoparticle Drug Delivery System Drug Evaluation, Preclinical Biological Products Drug Compounding Bayes Theorem
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A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection.

Computational and mathematical methods in medicine Sep 13, 2021
Artificial Intelligence (AI) is the domain of computer science that focuses on the development of machines that operate like humans. In the field of AI, medical disease detection is an instantly growing domain of research. In the past years, numerous...
Stochastic Processes Nonlinear Dynamics Diagnosis, Computer-Assisted Image Interpretation, Computer-Assisted Artificial Intelligence Humans Computational Biology Machine Learning Bayes Theorem Neural Networks, Computer Alzheimer Disease
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Application of a time-series deep learning model to predict cardiac dysrhythmias in electronic health records.

PloS one Sep 13, 2021
BACKGROUND: Cardiac dysrhythmias (CD) affect millions of Americans in the United States (US), and are associated with considerable morbidity and mortality. New strategies to combat this growing problem are urgently needed.
Arrhythmias, Cardiac United States Bayes Theorem Middle Aged Deep Learning Humans Female Aged Neural Networks, Computer Male Electronic Health Records
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Uncertainty propagation for dropout-based Bayesian neural networks.

Neural networks : the official journal of the International Neural Network Society Sep 9, 2021
Uncertainty evaluation is a core technique when deep neural networks (DNNs) are used in real-world problems. In practical applications, we often encounter unexpected samples that have not seen in the training process. Not only achieving the high-pred...
Uncertainty Bayes Theorem Monte Carlo Method Neural Networks, Computer Reproducibility of Results
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Retention time prediction in hydrophilic interaction liquid chromatography with graph neural network and transfer learning.

Journal of chromatography. A Sep 7, 2021
The combination of retention time (RT), accurate mass and tandem mass spectra can improve the structural annotation in untargeted metabolomics. However, the incorporation of RT for metabolite identification has received less attention because of the ...
Bayes Theorem Tandem Mass Spectrometry Machine Learning Neural Networks, Computer Hydrophobic and Hydrophilic Interactions Chromatography, Liquid
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Multitrait machine- and deep-learning models for genomic selection using spectral information in a wheat breeding program.

The plant genome Sep 5, 2021
Prediction of breeding values is central to plant breeding and has been revolutionized by the adoption of genomic selection (GS). Use of machine- and deep-learning algorithms applied to complex traits in plants can improve prediction accuracies. Beca...
Plant Breeding Triticum Genome, Plant Artificial Intelligence Genomics Deep Learning Bayes Theorem
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