AI Medical Compendium Topic

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

Rain

Showing 1 to 10 of 43 articles

Clear Filters

Meteorological and traffic effects on air pollutants using Bayesian networks and deep learning.

Journal of environmental sciences (China)
Traffic emissions have become the major air pollution source in urban areas. Therefore, understanding the highly non-stational and complex impact of traffic factors on air quality is very important for building air quality prediction models. Using re...

Multimodal Social Sensing for the Spatio-Temporal Evolution and Assessment of Nature Disasters.

Sensors (Basel, Switzerland)
Social sensing, using humans as sensors to collect disaster data, has emerged as a timely, cost-effective, and reliable data source. However, research has focused on the textual data. With advances in information technology, multimodal data such as i...

A predictive fuzzy logic and rule-based control approach for practical real-time operation of urban stormwater storage system.

Water research
Predictive real-time control (RTC) strategies are usually more effective than reactive strategies for the intelligent management of urban stormwater storage systems. However, it remains a challenge to ensure the practicality of RTC strategies that us...

Deciphering the climate-malaria nexus: A machine learning approach in rural southeastern Tanzania.

Public health
OBJECTIVES: Malaria remains a critical public health challenge, especially in regions like southeastern Tanzania. Understanding the intricate relationship between environmental factors and malaria incidence is essential for effective control and elim...

Enhancement of standardized precipitation evapotranspiration index predictions by machine learning based on regression and soft computing for Iran's arid and hyper-arid region.

PloS one
Drought is a climate risk that affects access to safe water, crop development, ecological stability, and food production. Therefore, developing drought prediction methods can lead to better management of surface and groundwater resources. Similarly, ...

Assessing the impact of rainfall, topography, and human disturbances on nutrient levels using integrated machine learning and GAMs models in the Choctawhatchee River Watershed.

Journal of environmental management
Nutrient pollution caused by excessive total nitrogen (TN) and total phosphorus (TP) is a significant environmental challenge globally, threatening water quality and ecosystem health. This study investigates the interplay between rainfall, topography...

Informing Risk Hotspots and Critical Mitigations for Rainstorms Using Machine Learning: Evidence from 268 Chinese Cities.

Environmental science & technology
Climate change is exacerbating rainstorms, increasing the risk of flooding and threatening urban sustainability, which could undermine climate action. Here, we propose a machine learning-based framework to assess heterogeneous risks and identify crit...

Cluster-based downscaling of precipitation using Kolmogorov-Arnold Neural Networks and CMIP6 models: Insights from Oman.

Journal of environmental management
Accurate precipitation predictions are crucial for addressing climate change impacts on water resources, especially in arid regions like Oman. Therefore, this study evaluates three machine learning models-Random Forest (RF), Multilayer Perceptron Neu...

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...

Image rain removal network based on checkerboard transformer and CNN hybrid mechanism.

PloS one
In this paper, a novel hybrid network called ChessFormer is proposed for the single image de-rain task. The network seamlessly integrates the advantages of Transformer and fitted neural network (CNN) in a checkerboard architecture, fully utilizing th...