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Forecasting

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Forecasting for Haditha reservoir inflow in the West of Iraq using Support Vector Machine (SVM).

PloS one
Accurate inflow forecasting is an essential non-engineering strategy to guarantee flood management and boost the effectiveness of the water supply. As inflow is the primary reservoir input, precise inflow forecasting may also offer appropriate reserv...

Machine-learning-based prediction by stacking ensemble strategy for surgical outcomes in patients with degenerative cervical myelopathy.

Journal of orthopaedic surgery and research
BACKGROUND: Machine learning (ML) is extensively employed for forecasting the outcome of various illnesses. The objective of the study was to develop ML based classifiers using a stacking ensemble strategy to predict the Japanese Orthopedic Associati...

The Future of Sustainable Neurosurgery: Is a Moonshot Plan for Artificial Intelligence and Robot-Assisted Surgery Possible in Japan?

World neurosurgery
Japanese neurosurgery faces challenges such as a declining number of neurosurgeons and their concentration in urban areas. Particularly in rural areas, access to neurosurgical care for patients with conditions, such as stroke, is limited, raising con...

Forecasting the incidence frequencies of schizophrenia using deep learning.

Asian journal of psychiatry
Mental disorders are becoming increasingly prevalent worldwide, and accurate incidence forecasting is crucial for effective mental health strategies. This study developed a long short-term memory (LSTM)-based recurrent neural network model to predict...

Artificial intelligence and the future of scientific publication.

European journal of emergency medicine : official journal of the European Society for Emergency Medicine

Real-time chlorophyll-a forecasting using machine learning framework with dimension reduction and hyperspectral data.

Environmental research
Since water is an essential resource in various fields, it requires constant monitoring. Chlorophyll-a concentration is a crucial indicator of water quality and can be used to monitor water quality. In this study, we developed methods to forecast chl...

Artificial Intelligence in Chronic Obstructive Pulmonary Disease: Research Status, Trends, and Future Directions --A Bibliometric Analysis from 2009 to 2023.

International journal of chronic obstructive pulmonary disease
OBJECTIVE: A bibliometric analysis was conducted using VOSviewer and CiteSpace to examine studies published between 2009 and 2023 on the utilization of artificial intelligence (AI) in chronic obstructive pulmonary disease (COPD).

From expansion to efficiency: Machine learning-based forecasting of Japan's building material stocks under demographic declines.

The Science of the total environment
Japan's unique demographic trajectory, marked by population decline and aging, coupled with continued urbanization, presents distinct challenges for aligning built environment capacity with resource efficiency. This study aims to investigate the hist...

Enhancing COVID-19 forecasting precision through the integration of compartmental models, machine learning and variants.

Scientific reports
Predicting epidemic evolution is essential for making informed decisions and guiding the implementation of necessary countermeasures. Computational models are vital tools that provide insights into illness progression and enable early detection, proa...

Accurate PM urban air pollution forecasting using multivariate ensemble learning Accounting for evolving target distributions.

Chemosphere
Over the past decades, air pollution has caused severe environmental and public health problems. According to the World Health Organization (WHO), fine particulate matter (PM), a key component reflecting air quality, is the fourth leading cause of de...