AIMC Topic: Forecasting

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Enhanced separation of long-term memory from short-term memory on top of LSTM: Neural network-based stock index forecasting.

PloS one Jun 2, 2025
LSTM (Long Short-Term Memory Network) is currently extensively utilized for forecasting financial time series, primarily due to its distinct advantages in separating the long-term from the short-term memory information within a sequence. However, the...
Humans Memory, Short-Term Investments Neural Networks, Computer Memory, Long-Term Forecasting
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Enhanced wheat yield prediction through integrated climate and satellite data using advanced AI techniques.

Scientific reports May 24, 2025
Wheat plays a vital role in Pakistan's economy and food security, making accurate yield forecasting essential for planning and resource management. Traditional approaches-such as manual field surveys and remote sensing-have been widely used, but thei...
Deep Learning Agriculture Remote Sensing Technology Machine Learning Forecasting Crops, Agricultural Climate Satellite Imagery Triticum Pakistan
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Forecasting malaria cases using climate variability in Sierra Leone.

Malaria journal May 20, 2025
BACKGROUND: Malaria continues to pose a public health challenge in Sierra Leone, where timely and accurate forecasting can guide more effective interventions. Although seasonal models such as Seasonal Autoregressive Integrated Moving Average (SARIMA)...
Models, Statistical Malaria Climate Humans Forecasting Sierra Leone Seasons Incidence Neural Networks, Computer
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Diagnosis of early idiopathic pulmonary fibrosis: current status and future perspective.

Respiratory research May 19, 2025
The standard approach to diagnosing idiopathic pulmonary fibrosis (IPF) includes identifying the usual interstitial pneumonia (UIP) pattern via high resolution computed tomography (HRCT) or lung biopsy and excluding known causes of interstitial lung ...
Humans Lung Idiopathic Pulmonary Fibrosis Bronchoscopy Forecasting Tomography, X-Ray Computed Early Diagnosis
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Dual-stream interactive networks with pearson-mask awareness for multivariate time series forecasting.

Neural networks : the official journal of the International Neural Network Society May 17, 2025
Multivariate time series forecasting (MTSF) aims to predict time series data containing multiple variates, which requires the consideration of both intra-series temporal trends and inter-series interactions. Benefiting from the success of Transformer...
Humans Neural Networks, Computer Time Factors Multivariate Analysis Forecasting
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Global burden of vertebral fractures from 1990 to 2021 and projections for the next three decades.

Journal of orthopaedic surgery and research May 17, 2025
BACKGROUND: Vertebral fractures are linked to significant disability and mortality risks. Yet, existing studies on their global burden are outdated and lack predictive foresight.
Cost of Illness Global Burden of Disease Incidence Spinal Fractures Adult Male Middle Aged Prevalence Global Health Female Aged Aged, 80 and over Humans Forecasting
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2024: A Year of Nursing Informatics Research in Review.

JMIR nursing May 7, 2025
Each year, nursing informatics researchers contribute to nursing and health informatics knowledge. The year 2024 emerged as yet another year of significant advances. In this editorial, I describe and highlight some of the key trends in nursing inform...
Nursing Research Forecasting Humans Nursing Informatics Artificial Intelligence
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Forecasting second-hand house prices in China using the GA-PSO-BP neural network model.

PloS one May 7, 2025
While the traditional genetic algorithms are capable of forecasting house prices, they often suffer from premature convergence, which adversely affects the reliability of the forecasts. To address this issue, the research employs a genetic-particle s...
Commerce Housing Humans Neural Networks, Computer Algorithms China Forecasting Models, Economic
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TCN-QV: an attention-based deep learning method for long sequence time-series forecasting of gold prices.

PloS one May 5, 2025
Accurate prediction of gold prices is crucial for investment decision-making and national risk management. The time series data of gold prices exhibits random fluctuations, non-linear characteristics, and high volatility, making prediction extremely ...
Deep Learning China Commerce Gold Humans Neural Networks, Computer Forecasting
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Comparison of dynamic mode decomposition with other data-driven models for lung cancer incidence rate prediction.

Frontiers in public health Apr 25, 2025
INTRODUCTION: Public health data analysis is critical to understanding disease trends. Existing analysis methods struggle with the complexity of public health data, which includes both location and time factors. Machine learning offers powerful tools...
United States Humans Support Vector Machine Forecasting Incidence Machine Learning Public Health Lung Neoplasms
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