AIMC Topic: Probability

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Holographic Declarative Memory: Distributional Semantics as the Architecture of Memory.

Cognitive science Nov 1, 2020
We demonstrate that the key components of cognitive architectures (declarative and procedural memory) and their key capabilities (learning, memory retrieval, probability judgment, and utility estimation) can be implemented as algebraic operations on ...
Humans Machine Learning Mental Recall Recognition, Psychology Probability Semantics Judgment Deep Learning Cognition Decision Making
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Deus Ex Machina? Predicting SARS-CoV-2 Infection from Lab Tests Using Machine Learning.

Clinical chemistry Nov 1, 2020
Reverse Transcriptase Polymerase Chain Reaction Coronavirus Infections COVID-19 Testing Algorithms Electronic Health Records SARS-CoV-2 Blood Cell Count Clinical Laboratory Techniques Humans Betacoronavirus Machine Learning Programming Languages Pneumonia, Viral Pandemics Laboratories COVID-19 Probability
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Augmenting Interpretation of Chest Radiographs With Deep Learning Probability Maps.

Journal of thoracic imaging Sep 1, 2020
PURPOSE: Pneumonia is a common clinical diagnosis for which chest radiographs are often an important part of the diagnostic workup. Deep learning has the potential to expedite and improve the clinical interpretation of chest radiographs. While earlie...
Adolescent Child, Preschool Child Infant Lung Deep Learning Radiography, Thoracic Pneumonia Radiographic Image Interpretation, Computer-Assisted Probability Aged Aged, 80 and over Young Adult Adult Male Middle Aged Humans Retrospective Studies Female
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Chemical-protein interaction extraction via Gaussian probability distribution and external biomedical knowledge.

Bioinformatics (Oxford, England) Aug 1, 2020
MOTIVATION: The biomedical literature contains a wealth of chemical-protein interactions (CPIs). Automatically extracting CPIs described in biomedical literature is essential for drug discovery, precision medicine, as well as basic biomedical researc...
Publications Data Mining Probability Neural Networks, Computer Research Design
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Validation of a Convolutional Neural Network Model for Spike Transformation Using a Generalized Linear Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Identification of causal relationships of neural activity is one of the most important problems in neuroscience and neural engineering. We show that a novel deep learning approach using a convolutional neural network to model output neural spike acti...
Neural Networks, Computer Action Potentials Neurons Probability Linear Models
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Modeling and measurement of signaling outcomes affecting decision making in noisy intracellular networks using machine learning methods.

Integrative biology : quantitative biosciences from nano to macro May 21, 2020
Characterization of decision-making in cells in response to received signals is of importance for understanding how cell fate is determined. The problem becomes multi-faceted and complex when we consider cellular heterogeneity and dynamics of biochem...
Outcome Assessment, Health Care Humans Probability Machine Learning PTEN Phosphohydrolase Signal Transduction Tumor Suppressor Protein p53 Algorithms Multivariate Analysis Decision Making Reproducibility of Results DNA Damage ROC Curve Genes, p53 Normal Distribution
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DEEPrior: a deep learning tool for the prioritization of gene fusions.

Bioinformatics (Oxford, England) May 1, 2020
SUMMARY: In the last decade, increasing attention has been paid to the study of gene fusions. However, the problem of determining whether a gene fusion is a cancer driver or just a passenger mutation is still an open issue. Here we present DEEPrior, ...
Proteins Probability Gene Fusion Software Deep Learning
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Structured Event Memory: A neuro-symbolic model of event cognition.

Psychological review Apr 1, 2020
Humans spontaneously organize a continuous experience into discrete events and use the learned structure of these events to generalize and organize memory. We introduce the (SEM) model of event cognition, which accounts for human abilities in event ...
Humans Generalization, Psychological Probability Neural Networks, Computer Memory Cognition Models, Psychological
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Bayesian framework for simulation of dynamical systems from multidimensional data using recurrent neural network.

Chaos (Woodbury, N.Y.) Dec 1, 2019
We suggest a new method for building data-driven dynamical models from observed multidimensional time series. The method is based on a recurrent neural network with specific structure, which allows for the joint reconstruction of both a low-dimension...
Probability Stochastic Processes Atmosphere Data Analysis Models, Theoretical Algorithms Neural Networks, Computer Bayes Theorem Computer Simulation Signal Processing, Computer-Assisted
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GUESS: projecting machine learning scores to well-calibrated probability estimates for clinical decision-making.

Bioinformatics (Oxford, England) Jul 15, 2019
MOTIVATION: Clinical decision support systems have been applied in numerous fields, ranging from cancer survival toward drug resistance prediction. Nevertheless, clinical decision support systems typically have a caveat: many of them are perceived as...
Machine Learning Probability Clinical Decision-Making Calibration Bayes Theorem
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