AIMC Topic: Disasters

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Evaluation of coseismic landslide susceptibility by combining Newmark model and XGBoost algorithm.

PloS one Aug 11, 2025
Coseismic landslides are among the most perilous geological disasters in hilly places after earthquakes. Precise assessment of coseismic landslide susceptibility is crucial for forecasting the effects of landslides and alleviating subsequent tragedie...
Algorithms Models, Theoretical Machine Learning Boosting Machine Learning Algorithms Landslides Earthquakes Monte Carlo Method Disasters
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Extreme Weather, Vulnerable Populations, and Mental Health: The Timely Role of AI Interventions.

International journal of environmental research and public health Apr 11, 2025
Environmental disasters are becoming increasingly frequent and severe, disproportionately impacting vulnerable populations who face compounded risks due to intersectional factors such as gender, socioeconomic status, rural residence, and cultural ide...
Disasters Vulnerable Populations Weather Humans Mental Health Artificial Intelligence
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Advanced susceptibility analysis of ground deformation disasters using large language models and machine learning: A Hangzhou City case study.

PloS one Dec 12, 2024
To address the prevailing scenario where comprehensive susceptibility assessments of ground deformation disasters primarily rely on knowledge-driven models, with weight judgments largely founded on expert subjective assessments, this study initially ...
Models, Theoretical Disasters Language Humans China Neural Networks, Computer Cities Machine Learning
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Assessment of urban flood susceptibility based on a novel integrated machine learning method.

Environmental monitoring and assessment Dec 5, 2024
Flood susceptibility assessment is the premise and foundation to prevent flood disaster events effectively. To accurately assess urban flood susceptibility (UFS), this study first analyzes the advantages and disadvantages of multi-layer perceptron (M...
Risk Assessment China Cities Machine Learning Disasters Logistic Models Floods Environmental Monitoring
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Application of artificial intelligence in triage in emergencies and disasters: a systematic review.

BMC public health Nov 18, 2024
INTRODUCTION AND OBJECTIVE: Modern and intelligent triage systems are used today due to the growing trend of disasters and emergencies worldwide and the increase in the number of injured people facing the challenge of using traditional triage methods...
Triage Disasters SARS-CoV-2 Emergencies Mass Casualty Incidents Artificial Intelligence COVID-19 Humans
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Multimodal Social Sensing for the Spatio-Temporal Evolution and Assessment of Nature Disasters.

Sensors (Basel, Switzerland) Sep 11, 2024
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...
Rain Natural Disasters Social Media Disasters Spatio-Temporal Analysis China Neural Networks, Computer Humans Risk Assessment
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Editorial: Artificial intelligence solutions for global health and disaster response: challenges and opportunities.

Frontiers in public health Aug 22, 2024
Global Health Disaster Planning Disasters Humans Artificial Intelligence
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Quantifying social capital creation in post-disaster recovery aid in Indonesia: methodological innovation by an AI-based language model.

Disasters Jun 11, 2024
Smooth interaction with a disaster-affected community can create and strengthen its social capital, leading to greater effectiveness in the provision of successful post-disaster recovery aid. To understand the relationship between the types of intera...
Humans Relief Work Artificial Intelligence Social Capital Indonesia Language Qualitative Research Disasters
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Toward QoS Monitoring in IoT Edge Devices Driven Healthcare-A Systematic Literature Review.

Sensors (Basel, Switzerland) Nov 1, 2023
Smart healthcare is altering the delivery of healthcare by combining the benefits of IoT, mobile, and cloud computing. Cloud computing has tremendously helped the health industry connect healthcare facilities, caregivers, and patients for information...
Disasters Industry Cloud Computing Artificial Intelligence Humans Delivery of Health Care
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Rock Crack Recognition Technology Based on Deep Learning.

Sensors (Basel, Switzerland) Jun 8, 2023
The changes in cracks on the surface of rock mass reflect the development of geological disasters, so cracks on the surface of rock mass are early signs of geological disasters such as landslides, collapses, and debris flows. To research geological d...
Disasters Geology Recognition, Psychology Technology Deep Learning
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