AIMC Topic: Computer Simulation
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Genome-wide prediction for complex traits under the presence of dominance effects in simulated populations using GBLUP and machine learning methods.
Journal of animal science
Jun 1, 2020
The aim of this study was to compare the predictive performance of the Genomic Best Linear Unbiased Predictor (GBLUP) and machine learning methods (Random Forest, RF; Support Vector Machine, SVM; Artificial Neural Network, ANN) in simulated populatio...
Making Sense of Computational Psychiatry.
The international journal of neuropsychopharmacology
May 27, 2020
In psychiatry we often speak of constructing "models." Here we try to make sense of what such a claim might mean, starting with the most fundamental question: "What is (and isn't) a model?" We then discuss, in a concrete measurable sense, what it mea...
Categorization of digitized artworks by media with brain programming.
Applied optics
May 10, 2020
This work describes the use of brain programming applied to the categorization problem of art media. The art categorization problem-from the standpoint of materials and techniques used by artists-presents a challenging task and is considered an open ...
Intelligent-assistant system for scleral spur location.
Applied optics
Apr 1, 2020
A system based on the use of two artificial neural networks (ANNs) to determine the location of the scleral spur of the human eye in ocular images generated by an ultrasound biomicroscopy is presented in this paper. The two ANNs establish a relations...
Extreme value theory of evolving phenomena in complex dynamical systems: Firing cascades in a model of a neural network.
Chaos (Woodbury, N.Y.)
Apr 1, 2020
We extend the scope of the dynamical theory of extreme values to include phenomena that do not happen instantaneously but evolve over a finite, albeit unknown at the onset, time interval. We consider complex dynamical systems composed of many individ...
Complex spatial navigation in animals, computational models and neuro-inspired robots.
Biological cybernetics
Apr 1, 2020
EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition.
Cognitive science
Apr 1, 2020
Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-ste...
Computer-assisted Diagnosis of Breast Cancer by Cell Network Matrix Extraction and Multilayer Perceptron Analysis.
Annals of clinical and laboratory science
Mar 1, 2020
OBJECTIVE: Diagnosis of breast cancer is based on identification of various morphologic features by histopathologic examination of the specimen. Ancillary immunohistochemical and molecular analyses provide additional information that is prognostic an...
Restoring chaos using deep reinforcement learning.
Chaos (Woodbury, N.Y.)
Mar 1, 2020
A catastrophic bifurcation in non-linear dynamical systems, called crisis, often leads to their convergence to an undesirable non-chaotic state after some initial chaotic transients. Preventing such behavior has been quite challenging. We demonstrate...
Machine Learning and Mechanistic Modeling for Prediction of Metastatic Relapse in Early-Stage Breast Cancer.
JCO clinical cancer informatics
Mar 1, 2020
PURPOSE: For patients with early-stage breast cancer, predicting the risk of metastatic relapse is of crucial importance. Existing predictive models rely on agnostic survival analysis statistical tools (eg, Cox regression). Here we define and evaluat...
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