AIMC Topic: Stochastic Processes

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Aedes-AI: Neural network models of mosquito abundance.

PLoS computational biology Nov 19, 2021
We present artificial neural networks as a feasible replacement for a mechanistic model of mosquito abundance. We develop a feed-forward neural network, a long short-term memory recurrent neural network, and a gated recurrent unit network. We evaluat...
Aedes Mosquito Vectors Stochastic Processes Population Dynamics Models, Biological Weather Neural Networks, Computer Databases, Factual Animals Spatio-Temporal Analysis Computational Biology United States Systems Analysis Humans Vector Borne Diseases
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Correspondence between neuroevolution and gradient descent.

Nature communications Nov 2, 2021
We show analytically that training a neural network by conditioned stochastic mutation or neuroevolution of its weights is equivalent, in the limit of small mutations, to gradient descent on the loss function in the presence of Gaussian white noise. ...
Algorithms Neural Networks, Computer Computer Simulation Mutation Stochastic Processes
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Efficient Prediction of Missed Clinical Appointment Using Machine Learning.

Computational and mathematical methods in medicine Oct 22, 2021
Public health and its related facilities are crucial for thriving cities and societies. The optimum utilization of health resources saves money and time, but above all, it saves precious lives. It has become even more evident in the present as the pa...
Appointments and Schedules No-Show Patients Stochastic Processes Logistic Models Area Under Curve Support Vector Machine Humans Algorithms Data Interpretation, Statistical Decision Trees Databases, Factual Neural Networks, Computer Bayes Theorem Computational Biology Machine Learning
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Competency of Neural Networks for the Numerical Treatment of Nonlinear Host-Vector-Predator Model.

Computational and mathematical methods in medicine Oct 4, 2021
The aim of this work is to introduce a stochastic solver based on the Levenberg-Marquardt backpropagation neural networks (LMBNNs) for the nonlinear host-vector-predator model. The nonlinear host-vector-predator model is dependent upon five classes, ...
Neural Networks, Computer Computer Simulation Vector Borne Diseases Animals Computational Biology Plant Diseases Models, Biological Stochastic Processes Nonlinear Dynamics Predatory Behavior Disease Vectors
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An Approach for Thoracic Syndrome Classification with Convolutional Neural Networks.

Computational and mathematical methods in medicine Sep 20, 2021
There have been remarkable changes in our lives and the way we perceive the world with advances in computing technology. Healthcare sector is evolving with the intervention of the latest computer-driven technology and has made a remarkable change in ...
Radiographic Image Interpretation, Computer-Assisted Syndrome Radiography, Thoracic Stochastic Processes Thoracic Diseases Machine Learning Databases, Factual Computational Biology Humans Neural Networks, Computer
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A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection.

Computational and mathematical methods in medicine Sep 13, 2021
Artificial Intelligence (AI) is the domain of computer science that focuses on the development of machines that operate like humans. In the field of AI, medical disease detection is an instantly growing domain of research. In the past years, numerous...
Humans Alzheimer Disease Diagnosis, Computer-Assisted Neural Networks, Computer Nonlinear Dynamics Computational Biology Artificial Intelligence Stochastic Processes Image Interpretation, Computer-Assisted Bayes Theorem Machine Learning
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Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction.

IEEE transactions on neural networks and learning systems Aug 31, 2021
Electronic health records (EHRs) are characterized as nonstationary, heterogeneous, noisy, and sparse data; therefore, it is challenging to learn the regularities or patterns inherent within them. In particular, sparseness caused mostly by many missi...
Neural Networks, Computer Algorithms Electronic Health Records Deep Learning Humans Stochastic Processes Uncertainty Hospital Mortality Computational Biology Predictive Value of Tests
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Dendritic normalisation improves learning in sparsely connected artificial neural networks.

PLoS computational biology Aug 9, 2021
Artificial neural networks, taking inspiration from biological neurons, have become an invaluable tool for machine learning applications. Recent studies have developed techniques to effectively tune the connectivity of sparsely-connected artificial n...
Dendrites Neurons Nerve Net Stochastic Processes Machine Learning Animals Deep Learning Computational Biology Models, Neurological Action Potentials Humans Neural Networks, Computer
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A stochastic modeling approach for analyzing water resources systems.

Journal of contaminant hydrology Aug 8, 2021
Many uncertain factors exist in the water resource systems, leading to dynamic characteristics of the water distribution process. Especially for the watershed including irrigation area with multiple water sources and water users, it is complicated th...
Water Resources Stochastic Processes Water Supply Uncertainty Fuzzy Logic Models, Theoretical Probability
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Deep Semisupervised Multitask Learning Model and Its Interpretability for Survival Analysis.

IEEE journal of biomedical and health informatics Aug 5, 2021
Survival analysis is a commonly used method in the medical field to analyze and predict the time of events. In medicine, this approach plays a key role in determining the course of treatment, developing new drugs, and improving hospital procedures. M...
Humans Supervised Machine Learning Survival Analysis Stochastic Processes
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