AIMC Topic: Forecasting

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[From global strategy to local consultation: A future vision of physical activity in primary care].

Atencion primaria
This article reflects on the key role that primary care must play in promoting physical activity as a central tool for health. Despite decades of international strategies, levels of physical inactivity and sedentary behavior continue to rise. The pri...

[Participatory approaches in the development of AI applications in medicine: opportunities and challenges].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
The increasing integration of artificial intelligence (AI) in healthcare not only holds the potential for efficiency gains, personalized medicine, and evidence-based decisions but also raises ethical and social challenges, such as bias, lack of trans...

ChatGPT-Assisted Deep Learning Models for Influenza-Like Illness Prediction in Mainland China: Time Series Analysis.

Journal of medical Internet research
BACKGROUND: Influenza in mainland China results in a large number of outpatient and emergency visits related to influenza-like illness (ILI) annually. While deep learning models show promise for improving influenza forecasting, their technical comple...

Decomposition-reconstruction-optimization framework for hog price forecasting: Integrating STL, PCA, and BWO-optimized BiLSTM.

PloS one
This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price serie...

PRformer: Pyramidal recurrent transformer for multivariate time series forecasting.

Neural networks : the official journal of the International Neural Network Society
The self-attention mechanism in Transformer architecture, invariant to sequence order, necessitates positional embeddings to encode temporal order in time series prediction. We argue that this reliance on positional embeddings restricts the Transform...

Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data.

PloS one
Population prediction could provide effective data support for social and economic planning and decision-making, especially for the sub-national population forecasting accurately. In addition to realizing efficient smart population management, this r...

Forecasting monthly residential natural gas demand in two cities of Turkey using just-in-time-learning modeling.

PloS one
Natural gas (NG) is relatively a clean source of energy, particularly compared to fossil fuels, and worldwide consumption of NG has been increasing almost linearly in the last two decades. A similar trend can also be seen in Turkey, while another sim...

Harmful Algae Forecasting through an Ocean Data Justice Lens.

Environmental science & technology
Forecasting systems for harmful algal blooms (HABs) are becoming more common, as HAB monitoring is increasingly networked and aggregated at national and global scales. Ocean forecasting programs in other fields have had unintended consequences and ou...

Enhancing corn industry sustainability through deep learning hybrid models for price volatility forecasting.

PloS one
The fluctuations in corn prices not only increase uncertainty in the market but also affect farmers' planting decisions and income stability, while also impeding crucial investments in sustainable agricultural practices. Collectively, these factors j...

Position of artificial intelligence in healthcare and future perspective.

Artificial intelligence in medicine
Artificial Intelligence (AI) has been used in healthcare with increasing momentum. According to a published report, 6.6 billion dollars were invested in AI healthcare in 2021, and this investment is expected to provide 150 billion dollars of benefit ...