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Bayes Theorem

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Automated cephalometric landmark detection with confidence regions using Bayesian convolutional neural networks.

BMC oral health Oct 7, 2020
BACKGROUND: Despite the integral role of cephalometric analysis in orthodontics, there have been limitations regarding the reliability, accuracy, etc. of cephalometric landmarks tracing. Attempts on developing automatic plotting systems have continuo...
Bayes Theorem Anatomic Landmarks Cephalometry Neural Networks, Computer Reproducibility of Results Image Processing, Computer-Assisted
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IAMPE: NMR-Assisted Computational Prediction of Antimicrobial Peptides.

Journal of chemical information and modeling Sep 30, 2020
Antimicrobial peptides (AMPs) are at the focus of attention due to their therapeutic importance and developing computational tools for the identification of efficient antibiotics from the primary structure. Here, we utilized the CNMR spectral of amin...
Computational Biology Support Vector Machine Bayes Theorem Amino Acids Algorithms Pore Forming Cytotoxic Proteins
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A machine learning Automated Recommendation Tool for synthetic biology.

Nature communications Sep 25, 2020
Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long develop...
Biofuels Saccharomyces cerevisiae Metabolic Engineering Fatty Acids Synthetic Biology Machine Learning Beer Escherichia coli Dodecanol Bayes Theorem
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Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Protein-Ligand Predictions.

Journal of chemical information and modeling Sep 21, 2020
In the context of bioactivity prediction, the question of how to calibrate a score produced by a machine learning method into a probability of binding to a protein target is not yet satisfactorily addressed. In this study, we compared the performance...
Bayes Theorem Ligands Probability Machine Learning Support Vector Machine
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Keeping up with the genomes: efficient learning of our increasing knowledge of the tree of life.

BMC bioinformatics Sep 21, 2020
BACKGROUND: It is a computational challenge for current metagenomic classifiers to keep up with the pace of training data generated from genome sequencing projects, such as the exponentially-growing NCBI RefSeq bacterial genome database. When new ref...
Metagenome Bayes Theorem Metagenomics Genome, Bacterial Gastrointestinal Microbiome Sequence Analysis, DNA Machine Learning Humans Algorithms Bacteria
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Biomechanical monitoring and machine learning for the detection of lying postures.

Clinical biomechanics (Bristol, Avon) Sep 20, 2020
BACKGROUND: Pressure mapping technology has been adapted to monitor over prolonged periods to evaluate pressure ulcer risk in individuals during extended lying postures. However, temporal pressure distribution signals are not currently used to identi...
Bayes Theorem Biomechanical Phenomena Mechanical Phenomena Movement Humans Male Machine Learning Posture
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Using Chou's 5-steps rule to identify N-methyladenine sites by ensemble learning combined with multiple feature extraction methods.

Journal of biomolecular structure & dynamics Sep 18, 2020
-methyladenine (m6A), a type of modification mostly affecting the downstream biological functions and determining the levels of gene expression, is mediated by the methylation of adenine in nucleic acids. It is also a key factor for influencing biolo...
Humans Machine Learning Algorithms Animals Mice Computational Biology Support Vector Machine Bayes Theorem Adenine
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Training deep neural density estimators to identify mechanistic models of neural dynamics.

eLife Sep 17, 2020
Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challen...
Bayes Theorem Animals Machine Learning Neurons Mice Neural Networks, Computer Algorithms Rats
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Development of Machine Learning Models to Validate a Medication Regimen Complexity Scoring Tool for Critically Ill Patients.

The Annals of pharmacotherapy Sep 15, 2020
INTRODUCTION: The Medication Regimen Complexity -Intensive Care Unit (MRC-ICU) is the first tool for measuring medication regimen complexity in critically ill patients. This study tested machine learning (ML) models to investigate the relationship be...
Hospitalization Aged Aged, 80 and over Intensive Care Units Female Hospital Mortality Bayes Theorem APACHE Adult Male Middle Aged Machine Learning Retrospective Studies Critical Illness Humans Medication Reconciliation
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Machine learning at the interface of structural health monitoring and non-destructive evaluation.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Sep 14, 2020
While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities...
Manufacturing and Industrial Facilities Robotics Bayes Theorem Signal Processing, Computer-Assisted Machine Learning Algorithms Humans Regression Analysis Ultrasonics Data Compression Engineering
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