AIMC Topic: Probability

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An EEG-Based Fuzzy Probability Model for Early Diagnosis of Alzheimer's Disease.

Journal of medical systems
Alzheimer's disease is a degenerative brain disease that results in cardinal memory deterioration and significant cognitive impairments. The early treatment of Alzheimer's disease can significantly reduce deterioration. Early diagnosis is difficult, ...

ProbOnto: ontology and knowledge base of probability distributions.

Bioinformatics (Oxford, England)
MOTIVATION: Probability distributions play a central role in mathematical and statistical modelling. The encoding, annotation and exchange of such models could be greatly simplified by a resource providing a common reference for the definition of pro...

Effect of network architecture on burst and spike synchronization in a scale-free network of bursting neurons.

Neural networks : the official journal of the International Neural Network Society
We investigate the effect of network architecture on burst and spike synchronization in a directed scale-free network (SFN) of bursting neurons, evolved via two independent α- and β-processes. The α-process corresponds to a directed version of the Ba...

Regular expressions for decoding of neural network outputs.

Neural networks : the official journal of the International Neural Network Society
This article proposes a convenient tool for decoding the output of neural networks trained by Connectionist Temporal Classification (CTC) for handwritten text recognition. We use regular expressions to describe the complex structures expected in the ...

Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting.

Journal of biomedical informatics
Models for predicting the probability of experiencing various health outcomes or adverse events over a certain time frame (e.g., having a heart attack in the next 5years) based on individual patient characteristics are important tools for managing pa...

Natural Language Processing for Cohort Discovery in a Discharge Prediction Model for the Neonatal ICU.

Applied clinical informatics
OBJECTIVES: Discharging patients from the Neonatal Intensive Care Unit (NICU) can be delayed for non-medical reasons including the procurement of home medical equipment, parental education, and the need for children's services. We previously created ...

Optimizing Semantic Pointer Representations for Symbol-Like Processing in Spiking Neural Networks.

PloS one
The Semantic Pointer Architecture (SPA) is a proposal of specifying the computations and architectural elements needed to account for cognitive functions. By means of the Neural Engineering Framework (NEF) this proposal can be realized in a spiking n...

What can Neighbourhood Density effects tell us about word learning? Insights from a connectionist model of vocabulary development.

Journal of child language
In this paper, we investigate the effect of neighbourhood density (ND) on vocabulary size in a computational model of vocabulary development. A word has a high ND if there are many words phonologically similar to it. High ND words are more easily lea...

A method for modeling co-occurrence propensity of clinical codes with application to ICD-10-PCS auto-coding.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Natural language processing methods for medical auto-coding, or automatic generation of medical billing codes from electronic health records, generally assign each code independently of the others. They may thus assign codes for closely re...

Chaotic Teaching-Learning-Based Optimization with Lévy Flight for Global Numerical Optimization.

Computational intelligence and neuroscience
Recently, teaching-learning-based optimization (TLBO), as one of the emerging nature-inspired heuristic algorithms, has attracted increasing attention. In order to enhance its convergence rate and prevent it from getting stuck in local optima, a nove...