AIMC Topic: Forecasting

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Artificial Intelligence May Cause a Significant Disruption to the Radiology Workforce.

Journal of the American College of Radiology : JACR Apr 8, 2019
The increasingly realistic prospect of artificial intelligence (AI) playing an important role in radiology has been welcomed with a mixture of enthusiasm and anxiousness. A consensus has arisen that AI will support radiologists in the interpretation ...
Workforce Artificial Intelligence Forecasting Humans Radiology
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Midterm Power Load Forecasting Model Based on Kernel Principal Component Analysis and Back Propagation Neural Network with Particle Swarm Optimization.

Big data Apr 8, 2019
To improve the accuracy of midterm power load forecasting, a forecasting model is proposed by combing kernel principal component analysis (KPCA) with back propagation neural network. First, the dimension of the input space is reduced by KPCA, then in...
Neural Networks, Computer Forecasting Support Vector Machine Principal Component Analysis
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Deep-learning for seizure forecasting in canines with epilepsy.

Journal of neural engineering Apr 8, 2019
OBJECTIVE: This paper introduces a fully automated, subject-specific deep-learning convolutional neural network (CNN) system for forecasting seizures using ambulatory intracranial EEG (iEEG). The system was tested on a hand-held device (Mayo Epilepsy...
Forecasting Animals Dogs Electrocorticography Electrodes, Implanted Deep Learning Epilepsy Seizures
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Forecasting future Humphrey Visual Fields using deep learning.

PloS one Apr 5, 2019
PURPOSE: To determine if deep learning networks could be trained to forecast future 24-2 Humphrey Visual Fields (HVFs).
Visual Field Tests Female Aged Humans Visual Fields Spatio-Temporal Analysis Glaucoma Adult Forecasting Linear Models Deep Learning Databases, Factual Algorithms Models, Statistical Male Middle Aged Disease Progression
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A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records.

BMC medical informatics and decision making Apr 4, 2019
BACKGROUND: Disease prediction based on Electronic Health Records (EHR) has become one hot research topic in biomedical community. Existing work mainly focuses on the prediction of one target disease, and little work is proposed for multiple associat...
Humans Kidney Diseases Neural Networks, Computer Risk Factors Forecasting Hypertension Electronic Health Records
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Concurrent, Performance-Based Methodology for Increasing the Accuracy and Certainty of Short-Term Neural Prediction Systems.

Computational intelligence and neuroscience Apr 1, 2019
Accurate prediction of the short time series with highly irregular behavior is a challenging task found in many areas of modern science. Such data fluctuations are not systematic and hardly predictable. In recent years, artificial neural networks hav...
Algorithms Humans Nonlinear Dynamics Forecasting Neural Networks, Computer Uncertainty Data Accuracy
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On-line prediction of ferrous ion concentration in goethite process based on self-adjusting structure RBF neural network.

Neural networks : the official journal of the International Neural Network Society Mar 29, 2019
Outlet ferrous ion concentration is an essential indicator to manipulate the goethite process in the zinc hydrometallurgy plant. However, it cannot be measured on-line, which leads to the delay of this feedback information. In this study, a self-adju...
Iron Compounds Metallurgy Neurons Ferrous Compounds Neural Networks, Computer Algorithms Forecasting Feedback Minerals
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Financial time series forecasting using twin support vector regression.

PloS one Mar 13, 2019
Financial time series forecasting is a crucial measure for improving and making more robust financial decisions throughout the world. Noisy data and non-stationarity information are the two key factors in financial time series prediction. This paper ...
Databases, Factual Time Factors Support Vector Machine Regression Analysis Financial Management Humans Decision Making, Computer-Assisted Forecasting Models, Economic Investments
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Risk-based postprandial hypoglycemia forecasting using supervised learning.

International journal of medical informatics Mar 11, 2019
BACKGROUND: Predicting insulin-induced postprandial hypoglycemic events is critical for the safety of type 1 diabetes patients because an early warning of hypoglycemia facilitates correction of the insulin bolus before its administration. The postpra...
Supervised Machine Learning Postprandial Period Insulin Infusion Systems Hypoglycemic Agents Hypoglycemia Retrospective Studies Female Male Blood Glucose Insulin Humans Diabetes Mellitus, Type 1 Forecasting
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Online learning with an almost perfect expert.

Proceedings of the National Academy of Sciences of the United States of America Mar 8, 2019
We study multiclass online learning, where a forecaster predicts a sequence of elements drawn from a finite set using the advice of n experts. Our main contributions are to analyze the scenario where the best expert makes a bounded number b of mistak...
Algorithms Forecasting Models, Theoretical Supervised Machine Learning
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