AIMC Topic: Bayes Theorem

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Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders.

Scientific reports Jul 3, 2020
Translational research of many disease areas requires a longitudinal understanding of disease development and progression across all biologically relevant scales. Several corresponding studies are now available. However, to compile a comprehensive pi...
Deep Learning User-Computer Interface Cohort Studies Brain Computer Simulation Disease Progression Models, Statistical Bayes Theorem Translational Research, Biomedical Alzheimer Disease Polymorphism, Single Nucleotide Longitudinal Studies Parkinson Disease Humans Databases, Factual
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Energy-efficient and damage-recovery slithering gait design for a snake-like robot based on reinforcement learning and inverse reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Jun 16, 2020
Similar to real snakes in nature, the flexible trunks of snake-like robots enhance their movement capabilities and adaptabilities in diverse environments. However, this flexibility corresponds to a complex control task involving highly redundant degr...
Algorithms Learning Gait Energy Metabolism Robotics Bayes Theorem Reinforcement, Psychology
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Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital.

Diagnostic microbiology and infectious disease Jun 8, 2020
Previous studies have shown promising results of machine learning (ML) models for predicting health outcomes. We develop and test ML models for predicting Clostridioides difficile infection (CDI) in hospitalized patients. This is a retrospective coho...
Clostridioides difficile Bayes Theorem Tertiary Care Centers Clostridium Infections ROC Curve Logistic Models Area Under Curve Humans Aged Machine Learning Male Anti-Bacterial Agents Forecasting Middle Aged Retrospective Studies Diarrhea Female
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Comparing Machine Learning Algorithms for Predicting Drug-Induced Liver Injury (DILI).

Molecular pharmaceutics Jun 8, 2020
Drug-induced liver injury (DILI) is one the most unpredictable adverse reactions to xenobiotics in humans and the leading cause of postmarketing withdrawals of approved drugs. To date, these drugs have been collated by the FDA to form the DILIRank da...
Humans Machine Learning Drug-Related Side Effects and Adverse Reactions Drug Approval Computer Simulation Chemical and Drug Induced Liver Injury Liver Bayes Theorem Software Algorithms Databases, Factual Databases, Pharmaceutical Biopharmaceutics
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Risk of a second wave of Covid-19 infections: using artificial intelligence to investigate stringency of physical distancing policies in North America.

International orthopaedics Jun 5, 2020
PURPOSE: Accurately forecasting the occurrence of future covid-19-related cases across relaxed (Sweden) and stringent (USA and Canada) policy contexts has a renewed sense of urgency. Moreover, there is a need for a multidimensional county-level appro...
Sweden Pneumonia, Viral Risk Factors Canada Physical Examination Coronavirus Infections Physical Distancing Pandemics Telemedicine Betacoronavirus COVID-19 United States SARS-CoV-2 Humans Bayes Theorem Artificial Intelligence
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Implementation of model explainability for a basic brain tumor detection using convolutional neural networks on MRI slices.

Neuroradiology Jun 4, 2020
PURPOSE: While neural networks gain popularity in medical research, attempts to make the decisions of a model explainable are often only made towards the end of the development process once a high predictive accuracy has been achieved.
Datasets as Topic Neurilemmoma Brain Neoplasms Contrast Media Magnetic Resonance Imaging Bayes Theorem Image Interpretation, Computer-Assisted Humans Diagnosis, Differential Neural Networks, Computer Glioblastoma
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Borrowing external information to improve Bayesian confidence propagation neural network.

European journal of clinical pharmacology Jun 1, 2020
PURPOSE: A Bayesian confidence propagation neural network (BCPNN) is a signal detection method used by the World Health Organization Uppsala Monitoring Centre to analyze spontaneous reporting system databases. We modify the BCPNN to increase its sens...
Humans Neural Networks, Computer Drug-Related Side Effects and Adverse Reactions Adverse Drug Reaction Reporting Systems Databases, Factual Computer Simulation Bayes Theorem
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A novel approach to modeling multifactorial diseases using Ensemble Bayesian Rule classifiers.

Journal of biomedical informatics Jun 1, 2020
Modeling factors influencing disease phenotypes, from biomarker profiling study datasets, is a critical task in biomedicine. Such datasets are typically generated from high-throughput 'omic' technologies, which help examine disease mechanisms at an u...
Bayes Theorem Machine Learning
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Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm.

Computers in biology and medicine May 30, 2020
MOTIVATION: Brain or central nervous system cancer is the tenth leading cause of death in men and women. Even though brain tumour is not considered as the primary cause of mortality worldwide, 40% of other types of cancer (such as lung or breast canc...
Magnetic Resonance Imaging Bayes Theorem Humans Brain Neoplasms Artificial Intelligence Male Female Deep Learning
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Using Artificial Intelligence for Pattern Recognition in a Sports Context.

Sensors (Basel, Switzerland) May 27, 2020
Optimizing athlete's performance is one of the most important and challenging aspects of coaching. Physiological and positional data, often acquired using wearable devices, have been useful to identify patterns, thus leading to a better understanding...
Athletic Performance Humans Pattern Recognition, Automated Sports Wearable Electronic Devices Neural Networks, Computer Bayes Theorem Deep Learning
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