AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Climate Change

Showing 21 to 30 of 154 articles

Clear Filters

Artificial intelligence in the era of planetary health: insights on its application for the climate change-mental health nexus in the Philippines.

International review of psychiatry (Abingdon, England)
This review explores the transformative potential of Artificial Intelligence (AI) in the light of evolving threats to planetary health, particularly the dangers posed by the climate crisis and its emerging mental health impacts, in the context of a c...

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...

The use of multiple evidence base methods to enrich climate change research and knowledge in the Arctic.

Ambio
Indigenous and local knowledge (ILK) is increasingly used along with scientific knowledge (SK) to understand climate change. The multi evidence base (MEB) offers ways of combining knowledge systems together. Nonetheless, there is little guidance on h...

Climate Sustainability through AI-Crypto Synergies and Energy Transition in the Digital Landscape to Cut 0.7 GtCOe by 2030.

Environmental science & technology
The rapid expansion of artificial intelligence (AI)-enabled systems and cryptocurrency mining poses significant challenges to climate sustainability due to energy-intensive operations relying on fossil-powered grids. This work investigates the strate...

Hybrid deep learning downscaling of GCMs for climate impact assessment and future projections in Oman.

Journal of environmental management
Accurate downscaling of global circulation models (GCMs) is critical for assessing the impacts of climate change and water resources management. In this research, Fourteen GCMs were evaluated through a Taylor diagram, including EC-Earth3-CC, ACCESS-C...

Identifying the combined impact of human activities and natural factors on China's avian species richness using interpretable machine learning methods.

Journal of environmental management
With human activities-derived escalating climate change and rapid urbanization, avian species face significant survival challenges. Understanding the impact of human activities and environmental drivers on avian species richness is critical for effec...

Spatial prediction of forest fires in India: a machine learning approach for improved risk assessment and early warning systems.

Environmental science and pollution research international
Forest fires pose a significant ecological and environmental threat globally, and India has seen a marked increase in both the frequency and severity of these events in recent years. This has led to extensive damage to natural resources, including fo...

Flood resilience through hybrid deep learning: Advanced forecasting for Taipei's urban drainage system.

Journal of environmental management
The escalating impacts of climate change have intensified extreme rainfall events, placing urban drainage systems under unprecedented pressure and increasing flood risks. Addressing these challenges requires advanced flood mitigation strategies, opti...

Interconnections, trend analysis and forecasting of water-air temperature with water level dynamics in Blue Moon Lake Valley: A statistical and machine learning approach.

Journal of environmental management
Glacier-fed lakes serve as vital indicators of climate change, yet their temperature and water level dynamics are insufficiently studied, particularly in high-altitude basins. Examining these interactions is fundamental for the effective management o...

Leveraging ML to predict climate change impact on rice crop disease in Eastern India.

Environmental monitoring and assessment
Rice crop disease is critical in precision agriculture due to various influencing components and unstable environments. The current study uses machine learning (ML) models to predict rice crop disease in Eastern India based on biophysical factors for...