AIMC Topic: Forecasting

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Developing a short-term prediction model for asthma exacerbations from Swedish primary care patients' data using machine learning - Based on the ARCTIC study.

Respiratory medicine
OBJECTIVE: The ability to predict impending asthma exacerbations may allow better utilization of healthcare resources, prevention of hospitalization and improve patient outcomes. We aimed to develop models using machine learning to predict risk of ex...

Addressing Biodisaster X Threats With Artificial Intelligence and 6G Technologies: Literature Review and Critical Insights.

Journal of medical Internet research
BACKGROUND: With advances in science and technology, biotechnology is becoming more accessible to people of all demographics. These advances inevitably hold the promise to improve personal and population well-being and welfare substantially. It is pa...

Hybrid LSTM Self-Attention Mechanism Model for Forecasting the Reform of Scientific Research in Morocco.

Computational intelligence and neuroscience
Education is the cultivation of people to promote and guarantee the development of society. Education reforms can play a vital role in the development of a country. However, it is crucial to continually monitor the educational model's performance by ...

Artificial intelligence in urological oncology: An update and future applications.

Urologic oncology
There continues to be rapid developments and research in the field of Artificial Intelligence (AI) in Urological Oncology worldwide. In this review we discuss the basics of AI, application of AI per tumour group (Renal, Prostate and Bladder Cancer) a...

A COVID-19 Pandemic Artificial Intelligence-Based System With Deep Learning Forecasting and Automatic Statistical Data Acquisition: Development and Implementation Study.

Journal of medical Internet research
BACKGROUND: More than 79.2 million confirmed COVID-19 cases and 1.7 million deaths were caused by SARS-CoV-2; the disease was named COVID-19 by the World Health Organization. Control of the COVID-19 epidemic has become a crucial issue around the glob...

Influenza forecasting for French regions combining EHR, web and climatic data sources with a machine learning ensemble approach.

PloS one
Effective and timely disease surveillance systems have the potential to help public health officials design interventions to mitigate the effects of disease outbreaks. Currently, healthcare-based disease monitoring systems in France offer influenza a...

Water quality assessment of a river using deep learning Bi-LSTM methodology: forecasting and validation.

Environmental science and pollution research international
Water is a prime necessity for the survival and sustenance of all living beings. Over the past few years, the water quality of rivers is adversely affected due to harmful wastes and pollutants. This ever-increasing water pollution is a big matter of ...

Robust Optimization and Validation of Echo State Networks for learning chaotic dynamics.

Neural networks : the official journal of the International Neural Network Society
An approach to the time-accurate prediction of chaotic solutions is by learning temporal patterns from data. Echo State Networks (ESNs), which are a class of Reservoir Computing, can accurately predict the chaotic dynamics well beyond the predictabil...

AQI time series prediction based on a hybrid data decomposition and echo state networks.

Environmental science and pollution research international
A hybrid AQI time series prediction model is proposed based on EWT-SE-VMD secondary decomposition, ICA (imperialist competitive algorithm) feature selection, and ESN (echo state network) neural network. Firstly, EWT (empirical wavelet transform) and ...