AIMC Topic: Forecasting

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Clinical approaches for integrating machine learning for patients with lymphoma: Current strategies and future perspectives.

British journal of haematology
Machine learning (ML) approaches have been applied in the diagnosis and prediction of haematological malignancies. The consideration of ML algorithms to complement or replace current standard of care approaches requires investigation into the methods...

A comparative study of data-driven models for runoff, sediment, and nitrate forecasting.

Journal of environmental management
Effective prediction of qualitative and quantitative indicators for runoff is quite essential in water resources planning and management. However, although several data-driven and model-driven forecasting approaches have been employed in the literatu...

Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects.

European radiology experimental
Artificial intelligence (AI) is transforming the field of medical imaging and has the potential to bring medicine from the era of 'sick-care' to the era of healthcare and prevention. The development of AI requires access to large, complete, and harmo...

Application of grey feed forward back propagation-neural network model based on wavelet denoising to predict the residual settlement of goafs.

PloS one
To study the residual settlement of goaf's law and prediction model, we investigated the Mentougou mining area in Beijing as an example. Using MATLAB software, the wavelet threshold denoising method was used to optimize measured data, and the grey mo...

Characteristic mango price forecasting using combined deep-learning optimization model.

PloS one
Accurate product price forecasting is helpful for scientific decision-making and precise industrial planning. As a characteristic fruit that drives regional development, mango price prediction is of great significance to several economies. However, o...

A Prediction Model Based on Gated Nonlinear Spiking Neural Systems.

International journal of neural systems
Nonlinear spiking neural P (NSNP) systems are one of neural-like membrane computing models, abstracted by nonlinear spiking mechanisms of biological neurons. NSNP systems have a nonlinear structure and can show rich nonlinear dynamics. In this paper,...

Comparing machine learning methods for predicting land development intensity.

PloS one
Land development intensity is a comprehensive indicator to measure the degree of saving and intensive land construction and economic production activities. It is also the result of the joint action of natural, social, economic, and ecological element...

Enhanced rainfall prediction performance via hybrid empirical-singular-wavelet-fuzzy approaches.

Environmental science and pollution research international
Rainfall is a vital process in the hydrological cycle of the globe. Accessing reliable and accurate rainfall data is crucial for water resources operation, flood control, drought warning, irrigation, and drainage. In the present study, the main objec...

Introduction to Radiomics and Artificial Intelligence: A Primer for Radiologists.

Seminars in roentgenology
Health informatics and artificial intelligence (AI) are expected to transform the healthcare enterprise and the future practice of radiology. There is an increasing body of literature on radiomics and deep learning/AI applications in medical imaging....