AIMC Topic: Climate Change

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Comparative analysis of machine learning approaches for heatwave event prediction in India.

Scientific reports
Heatwaves, are identified as prolonged durations of unusually high temperatures, which pose significant threats to human health, animal health and agriculture. With the increasing frequency and intensity of heatwaves driven by climate change, accurat...

Environmental drivers of calling activity in the critically endangered lemur leaf frog, (Hylidae: Phyllomedusinae).

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Tropical frog species are known to exhibit high sensitivity to weather regime alterations, which leaves them vulnerable to ongoing climate change. This challenge is exacerbated by limited knowledge of species-specific responses to environmental chang...

Spatiotemporal patterns and climate-induced macroeconomic burden of malaria in sub-Saharan Africa.

BMC public health
BACKGROUND: The global malaria burden is characterized by economic, geographical, and climatic disparities, especially in sub-Saharan Africa (SSA). Moreover, meteorological factors have become increasingly important to understand the malaria burden i...

Aligning With the Goals of the Planetary Health Concept Regarding Ecological Sustainability and Digital Health: Scoping Review.

Journal of medical Internet research
BACKGROUND: Climate change, driven by greenhouse gas emissions, threatens human health and biodiversity. While the digitalization of health care, including telemedicine and artificial intelligence, offers sustainability benefits, it also raises conce...

Modeling climate change impacts and predicting future vulnerability in the Mount Kenya forest ecosystem using remote sensing and machine learning.

Environmental monitoring and assessment
The Mount Kenya forest ecosystem (MKFE), a crucial biodiversity hotspot and one of Kenya's key water towers, is increasingly threatened by climate change, putting its ecological integrity and vital ecosystem services at risk. Understanding the intera...

Using large language models to learn from recent climate change discourse in public health.

PloS one
BACKGROUND: Public health has increasingly recognized the links between climate change and health, emphasizing the need to address related inequities. This is reflected in work led by the Intergovernmental Panel on Climate Change, the UN Framework Co...

Harnessing deep learning to monitor people's perceptions towards climate change on social media.

Scientific reports
Social media has become a popular stage for people's views over climate change. Monitoring how climate change is perceived on social media is relevant for informed decision-making. This work advances the way social media users' perceptions and reacti...

Deep learning-based spatial optimization of green and cool roof implementation for urban heat mitigation.

Journal of environmental management
Intensifying urban heat extremes require efficient mitigation strategies; therefore, we propose a methodological framework for optimizing the implementation of urban green and cool roofs to reduce heat stress while maximizing their cost-effectiveness...

A sustainable industrial waste control with AI for predicting CO2 for climate change monitoring.

Journal of environmental management
As the challenge of climate change continues to grow, we need creative solutions to predict better and track industrial waste carbon emissions, focusing on sustainable waste management practices. The present study proposes a state-of-the-art Metavers...

A thematic analysis of what Australians state would change their minds on climate change.

Scientific reports
What do Australians believe would change their current opinions about climate change? In this study, we used audience segmentation analysis through the Six Americas Short Survey to identify groups of climate opinion holders within a representative sa...