Avian influenza (AI) is a viral infection that profoundly affects global poultry production. This study aimed to identify the spatial and temporal factors associated with AI in Thailand, using a geographic information system (GIS)-based multi-criteri...
Colorectal cancer (CRC) is a major health concern, ranking as the third deadliest cancer globally. Early diagnosis of adenomatous polyps which are pre-cancerous abnormal tissue growth, is crucial for preventing CRC. Artificial intelligence-assisted n...
Analysing the genome, epigenome, transcriptome, proteome, and metabolome within the spatial context of cells has transformed our understanding of tumour spatiotemporal heterogeneity. Advances in spatial multi-omics technologies now reveal complex mol...
With the acceleration of urbanization and the increase in traffic volume, frequent traffic accidents have significantly impacted public safety and socio-economic conditions. Traditional methods for predicting traffic accidents often overlook spatiote...
Under the increasing pressure of global climate change, water conservation (WC) in semi-arid regions is experiencing unprecedented levels of stress. WC involves complex, nonlinear interactions among ecosystem components like vegetation, soil structur...
The prevention of falls is paramount in modern healthcare, particularly for the elderly, as falls can lead to severe injuries or even fatalities. Additionally, the growing incidence of falls among the elderly, coupled with the urgent need to prevent ...
The outbreak of infectious diseases can have profound impacts on socio-economic balances globally. Accurate short-term forecasting of infectious diseases is crucial for policymakers and healthcare systems. This study proposes a novel deep learning ap...
As an important atmospheric pollutant causing serious harm to human health and the natural environment, monitoring of surface NO (SNO) level is of critical importance. However, the current SNO retrieval models neglect to consider the influence of NO ...
Most conventional crash severity models attempt to achieve a low classification error rate, implicitly assuming the same losses for all classification errors. In this paper, we suggest that this setting has limitations in terms of reasonableness, as ...
Computer methods and programs in biomedicine
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BACKGROUND AND OBJECTIVES: Electrophysiological source imaging (ESI) is a challenging technique for noninvasively measuring brain activity, which involves solving a highly ill-posed inverse problem. Traditional methods attempt to address this challen...