AIMC Topic: Forecasting

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Machine learning-based analysis and prediction of meteorological factors and urban heatstroke diseases.

Frontiers in public health
INTRODUCTION: Heatstroke is a serious clinical condition caused by exposure to high temperature and high humidity environment, which leads to a rapid increase of the core temperature of the body to more than 40°C, accompanied by skin burning, conscio...

Short- and long-term weather prediction based on a hybrid of CEEMDAN, LMD, and ANN.

PloS one
Agriculture is one of the major economic sectors in Africa, and it predominantly depends on the climate. However, extreme climate changes do have a negative impact on agricultural production. The damage resulting from extreme climate change can be mi...

The Current Application and Future Potential of Artificial Intelligence in Renal Cancer.

Urology
Artificial intelligence (AI) is the integration of human tasks into machine processes. The role of AI in kidney cancer evaluation, management, and outcome predictions are constantly evolving. We performed a narrative review utilizing PubMed electroni...

Adaptive Decision Spatio-temporal neural ODE for traffic flow forecasting with Multi-Kernel Temporal Dynamic Dilation Convolution.

Neural networks : the official journal of the International Neural Network Society
Traffic flow prediction is crucial for efficient traffic management. It involves predicting vehicle movement patterns to reduce congestion and enhance traffic flow. However, the highly non-linear and complex patterns commonly observed in traffic flow...

MGLEP: Multimodal Graph Learning for Modeling Emerging Pandemics with Big Data.

Scientific reports
Accurate forecasting and analysis of emerging pandemics play a crucial role in effective public health management and decision-making. Traditional approaches primarily rely on epidemiological data, overlooking other valuable sources of information th...

Predicting pharmaceutical prices. Advances based on purchase-level data and machine learning.

BMC public health
BACKGROUND: Increased costs in the health sector have put considerable strain on the public budgets allocated to pharmaceutical purchases. Faced with such pressures amplified by financial crises and pandemics, national purchasing authorities are pres...

Physics-informed machine learning algorithms for forecasting sediment yield: an analysis of physical consistency, sensitivity, and interpretability.

Environmental science and pollution research international
The sediment transport, involving the movement of the bedload and suspended sediment in the basins, is a critical environmental concern that worsens water scarcity and leads to degradation of land and its ecosystems. Machine learning (ML) algorithms ...

Research on short-term power load forecasting based on VMD and GRU.

PloS one
The traditional method for power load forecasting is susceptible to various factors, including holidays, seasonal variations, weather conditions, and more. These factors make it challenging to ensure the accuracy of forecasting results. Additionally,...

A novel approach to forecast surgery durations using machine learning techniques.

Health care management science
This study presents a methodology for predicting the duration of surgical procedures using Machine Learning (ML). The methodology incorporates a new set of predictors emphasizing the significance of surgical team dynamics and composition, including e...

Predicting Future Birth Rates with the Use of an Adaptive Machine Learning Algorithm: A Forecasting Experiment for Scotland.

International journal of environmental research and public health
The total fertility rate is influenced over an extended period of time by shifts in population socioeconomic characteristics and attitudes and values. However, it may be impacted by macroeconomic trends in the short term, although these effects are l...