AIMC Topic: Forecasting

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Is robotic assistance the future of percutaneous interventional radiology?

Diagnostic and interventional imaging Feb 24, 2024
Radiography, Interventional Humans Radiology, Interventional Forecasting Robotics Robotic Surgical Procedures
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TCDformer: A transformer framework for non-stationary time series forecasting based on trend and change-point detection.

Neural networks : the official journal of the International Neural Network Society Feb 23, 2024
Although time series prediction models based on Transformer architecture have achieved significant advances, concerns have arisen regarding their performance with non-stationary real-world data. Traditional methods often use stabilization techniques ...
Neural Networks, Computer Forecasting Time Factors
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Modelling the GDP of KSA using linear and non-linear NNAR and hybrid stochastic time series models.

PloS one Feb 23, 2024
BACKGROUND: Gross domestic product (GDP) serves as a crucial economic indicator for measuring a country's economic growth, exhibiting both linear and non-linear trends. This study aims to analyze and propose an efficient and accurate time series appr...
Time Factors Models, Statistical Gross Domestic Product Neural Networks, Computer Forecasting Incidence
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Deep learning applications for kidney histology analysis.

Current opinion in nephrology and hypertension Feb 19, 2024
PURPOSE OF REVIEW: Nephropathology is increasingly incorporating computational methods to enhance research and diagnostic accuracy. The widespread adoption of digital pathology, coupled with advancements in deep learning, will likely transform our pa...
Kidney Humans Kidney Diseases Forecasting Deep Learning
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Precision forecasting of spray-dry desulfurization using Gaussian noise data augmentation and k-fold cross-validation optimized neural computing.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering Feb 19, 2024
Perceptron models have become integral tools for pattern recognition and classification problems in engineering fields. This study envisioned implementing artificial neural networks to forecast the performance of a mini-spray dryer for desulfurizatio...
Temperature Neural Networks, Computer Forecasting Computer Simulation
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[Artificial intelligence-enhanced electrocardiography : Will it revolutionize diagnosis and management of our patients?].

Herzschrittmachertherapie & Elektrophysiologie Feb 15, 2024
The use of artificial intelligence (AI) in healthcare has made significant progress in the last 10 years. Many experts believe that utilization of AI technologies, especially deep learning, will bring about drastic changes in how physicians understan...
Forecasting Diagnosis, Computer-Assisted Electrocardiography Humans Artificial Intelligence
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Which model is more efficient in carbon emission prediction research? A comparative study of deep learning models, machine learning models, and econometric models.

Environmental science and pollution research international Feb 15, 2024
Accurately predicting future carbon emissions is of great significance for the government to scientifically promote carbon emission reduction policies. Among the current technologies for forecasting carbon emissions, the most prominent ones are econo...
China Carbon Models, Econometric Forecasting Deep Learning Machine Learning Neural Networks, Computer
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Comparing ARIMA and various deep learning models for long-term water quality index forecasting in Dez River, Iran.

Environmental science and pollution research international Feb 14, 2024
Water scarcity poses a significant global challenge, particularly in developing nations like Iran. Consequently, there is a pressing requirement for ongoing monitoring and prediction of water quality, utilizing advanced techniques characterized by lo...
Iran Water Quality Deep Learning Environmental Monitoring Rivers Forecasting
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Accuracy of artificial intelligence-assisted growth prediction in skeletal Class I preadolescent patients using serial lateral cephalograms for a 2-year growth interval.

Orthodontics & craniofacial research Feb 6, 2024
OBJECTIVE: To investigate the accuracy of artificial intelligence-assisted growth prediction using a convolutional neural network (CNN) algorithm and longitudinal lateral cephalograms (Lat-cephs).
Neural Networks, Computer Artificial Intelligence Humans Malocclusion, Angle Class I Maxillofacial Development Child Mandible Anatomic Landmarks Female Algorithms Cephalometry Male Forecasting
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Forecasting China carbon price using an error-corrected secondary decomposition hybrid model integrated fuzzy dispersion entropy and deep learning paradigm.

Environmental science and pollution research international Feb 6, 2024
Forecasting China's carbon price accurately can encourage investors and manufacturing industries to take quantitative investments and emission reduction decisions effectively. The inspiration for this paper is developing an error-corrected carbon pri...
Forecasting Deep Learning Entropy China Investments Carbon
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