AIMC Topic: Forecasting

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Artificial intelligence in surgery: evolution, trends, and future directions.

International journal of surgery (London, England)
Artificial intelligence (AI) is significantly transforming surgery by enhancing precision, decision-making, and patient outcomes. This bibliometric analysis examines AI's impact on surgery, highlighting research trends, key contributors, and evolving...

Integrating deep learning algorithms for forecasting evapotranspiration and assessing crop water stress in agricultural water management.

Journal of environmental management
The increasing impacts of climate change on global agriculture necessitate the development of advanced predictive models for efficient water management in crop fields. This study aims to enhance the forecasting of evapotranspiration (ET), potential e...

Using machine learning to forecast peak health care service demand in real-time during the 2022-23 winter season: A pilot in England, UK.

PloS one
During winter months, there is increased pressure on health care systems in temperature climates due to seasonal increases in respiratory illnesses. Providing real-time short-term forecasts of the demand for health care services helps managers plan t...

The feasibility of using machine learning to predict COVID-19 cases.

International journal of medical informatics
BACKGROUND: Coronavirus Disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, emerged as a global health crisis in 2019, resulting in widespread morbidity and mortality. A persistent challenge during the pandemic has been the accuracy of reported ...

Machine Learning Potential for Identifying and Forecasting Complex Environmental Drivers of Infections in the United States.

Environmental health perspectives
BACKGROUND: Environmental change in coastal areas can drive marine bacteria and resulting infections, such as those caused by , with both foodborne and nonfoodborne exposure routes and high mortality. Although ecological drivers of in the environmen...

Embracing the Future of Clinical Trials in Radiation Therapy: An NRG Oncology CIRO Technology Retreat Whitepaper on Pioneering Technologies and AI-Driven Solutions.

International journal of radiation oncology, biology, physics
This white paper examines the potential of pioneering technologies and artificial intelligence-driven solutions in advancing clinical trials involving radiation therapy. As the field of radiation therapy evolves, the integration of cutting-edge appro...

Time series forecasting of bed occupancy in mental health facilities in India using machine learning.

Scientific reports
Machine learning models are vital for forecasting and optimizing healthcare parameters, especially in the context of rising mental health issues in India and globally. With increasing demand for mental health services, effective resource management, ...

Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions.

BMC medical informatics and decision making
BACKGROUND: Post bariatric hypoglycaemic (PBH) is a late complication of weight loss surgery, characterised by critically low blood glucose levels following meal-induced glycaemic excursions. The disabling consequences of PBH underline the need for t...

MDWConv:CNN based on multi-scale atrous pyramid and depthwise separable convolution for long time series forecasting.

Neural networks : the official journal of the International Neural Network Society
Long time series forecasting has extensive applications in various fields such as power dispatching, traffic control, and weather forecasting. Recently, models based on the Transformer architecture have dominated the field of time series forecasting....

An ensemble deep learning framework for energy demand forecasting using genetic algorithm-based feature selection.

PloS one
Accurate energy demand forecasting is critical for efficient energy management and planning. Recent advancements in computing power and the availability of large datasets have fueled the development of machine learning models. However, selecting the ...