AI Medical Compendium Topic

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DEEPrior: a deep learning tool for the prioritization of gene fusions.

Bioinformatics (Oxford, England)
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, ...

Structured Event Memory: A neuro-symbolic model of event cognition.

Psychological review
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 ...

Bayesian framework for simulation of dynamical systems from multidimensional data using recurrent neural network.

Chaos (Woodbury, N.Y.)
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...

GUESS: projecting machine learning scores to well-calibrated probability estimates for clinical decision-making.

Bioinformatics (Oxford, England)
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...

Optimizing Probability Threshold of Convolution Neural Network to Improve HRV-based Acute Stress Detection Performance.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
As stress is linked to numerous emotional and physical conditions, its timely detection and proper management is important for our health. Convolution neural network (CNN) has been shown to be promising in stress detection because it could automatica...

Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We describe and assess convolutional neural network (CNN) models for detection of glaucoma based upon optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability maps. CNNs pretrained on natural images performed comparably to CNNs...

Deep Q-learning for Predicting Asthma Attack with Considering Personalized Environmental Triggers' Risk Scores.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The purpose of our present study was to develop a forecasting method that would help asthmatic individuals to take evasive action when the probability of an attack was at THEIR PERSONAL THRESHOLD levels. The results are encouraging. Risk factor analy...

Common Audiological Functional Parameters (CAFPAs): statistical and compact representation of rehabilitative audiological classification based on expert knowledge.

International journal of audiology
OBJECTIVE: As a step towards objectifying audiological rehabilitation and providing comparability between different test batteries and clinics, the Common Audiological Functional Parameters (CAFPAs) were introduced as a common and abstract representa...

On discrete time Beverton-Holt population model with fuzzy environment.

Mathematical biosciences and engineering : MBE
In this work, dynamical behaviors of discrete time Beverton-Holt population model with fuzzy parameters are studied. It provides a flexible model to fit population data. For three different fuzzy parameters and fuzzy initial conditions, according to ...

Causal models adjusting for time-varying confounding-a systematic review of the literature.

International journal of epidemiology
BACKGROUND: Obtaining unbiased causal estimates from longitudinal observational data can be difficult due to exposure-affected time-varying confounding. The past decade has seen considerable development in methods for analysing such complex longitudi...