AIMC Topic:
Bayes Theorem

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Machine learning for phytopathology: from the molecular scale towards the network scale.

Briefings in bioinformatics Sep 2, 2021
With the increasing volume of high-throughput sequencing data from a variety of omics techniques in the field of plant-pathogen interactions, sorting, retrieving, processing and visualizing biological information have become a great challenge. Within...
Bayes Theorem Bacterial Proteins NLR Proteins Support Vector Machine Protein Serine-Threonine Kinases Viral Proteins Protein Interaction Mapping Disease Resistance Pathogen-Associated Molecular Pattern Molecules Plant Pathology Receptors, Pattern Recognition Gene Expression Regulation Fungal Proteins Host-Pathogen Interactions Plants Plant Diseases
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A comprehensive overview and critical evaluation of gene regulatory network inference technologies.

Briefings in bioinformatics Sep 2, 2021
Gene regulatory network (GRN) is the important mechanism of maintaining life process, controlling biochemical reaction and regulating compound level, which plays an important role in various organisms and systems. Reconstructing GRN can help us to un...
Transcriptome RNA-Seq Gene Regulatory Networks Machine Learning Databases, Genetic Biomarkers, Tumor Computational Biology Bayes Theorem Neoplasms Models, Genetic Gene Expression Regulation Escherichia coli
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A Bayesian optimization approach for rapidly mapping residual network function in stroke.

Brain : a journal of neurology Aug 17, 2021
Post-stroke cognitive and linguistic impairments are debilitating conditions, with limited therapeutic options. Domain-general brain networks play an important role in stroke recovery and characterizing their residual function with functional MRI has...
Brain Mapping Bayes Theorem Stroke Male Middle Aged Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Humans Machine Learning Brain Female Aged Adult
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Asynchronous parallel Bayesian optimization for AI-driven cloud laboratories.

Bioinformatics (Oxford, England) Jul 12, 2021
MOTIVATION: The recent emergence of cloud laboratories-collections of automated wet-lab instruments that are accessed remotely, presents new opportunities to apply Artificial Intelligence and Machine Learning in scientific research. Among these is th...
Artificial Intelligence Software Algorithms Bayes Theorem Laboratories
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Joint Associations of Multiple Dietary Components With Cardiovascular Disease Risk: A Machine-Learning Approach.

American journal of epidemiology Jul 1, 2021
The human diet consists of a complex mixture of components. To realistically assess dietary impacts on health, new statistical tools that can better address nonlinear, collinear, and interactive relationships are necessary. Using data from 1,928 heal...
Heart Disease Risk Factors Linear Models Diet Surveys Follow-Up Studies Bayes Theorem Cardiovascular Diseases Middle Aged Risk Assessment Diet Female Humans United States Longitudinal Studies Adult Machine Learning Male Prospective Studies
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Probabilistic Contextual and Structural Dependencies Learning in Grammar-Based Genetic Programming.

Evolutionary computation Jun 1, 2021
Genetic Programming is a method to automatically create computer programs based on the principles of evolution. The problem of deceptiveness caused by complex dependencies among components of programs is challenging. It is important because it can mi...
Bayes Theorem Machine Learning Software Algorithms Neural Networks, Computer
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On the Efficiency of Machine Learning Models in Malaria Prediction.

Studies in health technology and informatics May 27, 2021
Malaria is still a real public health concern in Sub-Saharan African countries such as Senegal where it represents approximately 35% of the consultation activities in the hospitals. This is mainly due to the lack of appropriate medical care support a...
Humans Machine Learning Algorithms Bayes Theorem Malaria Senegal
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Clustering Results Interpretation of Continuous Variables Using Bayesian Inference.

Studies in health technology and informatics May 27, 2021
The present study is devoted to interpretable artificial intelligence in medicine. In our previous work we proposed an approach to clustering results interpretation based on Bayesian Inference. As an application case we used clinical pathways cluster...
Bayes Theorem Artificial Intelligence Algorithms Cluster Analysis
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Application of Bayesian networks to generate synthetic health data.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: This study seeks to develop a fully automated method of generating synthetic data from a real dataset that could be employed by medical organizations to distribute health data to researchers, reducing the need for access to real data. We h...
Data Anonymization Neural Networks, Computer Humans Information Dissemination Disclosure Data Management Datasets as Topic Machine Learning Bayes Theorem Confidentiality
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Inter classifier comparison to detect voice pathologies.

Mathematical biosciences and engineering : MBE Mar 5, 2021
Voice pathologies are irregular vibrations produced due to vocal folds and various factors malfunctioning. In medical science, novel machine learning algorithms are applied to construct a system to identify disorders that occur invoice. This study ai...
Machine Learning Support Vector Machine Algorithms Bayes Theorem
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