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Abstract Precise extraction of medical phenotypes and entities from electronic health record (EHR) text is vital for numerous clinical research tasks, including cohort classification, tracking temporal patterns in diseas...

Abstract Substation drawings are high-density technical artifacts that serve as the authoritative data source across the entire power-infrastructure lifecycle. Manual auditing of these drawings is labor-intensive, error-...

In semi-arid environments there is often a lack of data on hydrological variables that limits the ability to understand key hydrological processes. In response to this need, geomorphometric analysis is a quantitative app...

Abstract Early small fires in coal mines are of critical importance for mine safety, as most incidents begin as small fire sources. These fires essentially constitute a task of small-object detection. Detecting such targ...

Abstract Satellite Image Classification is a process in remote sensing that aims at classifying pixels of satellite imagery into usable information of land use and land cover. This information is not only limited to seve...

Runoff, groundwater recharge and discharge, and surface water-groundwater interaction are the main driving forces of wetlands. The quantification of such flows is crucial information in the restoration and management of ...

Abstract Long-range dependency processing is the core challenge of sequence modeling, and traditional sequence modeling algorithms suffer from information decay and low parallel computing efficiency in ultra long sequenc...

Abstract Accurate prediction of cascading faults in power grids can ensure system stability and prevent large-scale outages. Existing methods typically require learning effective statistical information from datasets wit...

Abstract Accurate differentiation of pulmonary emphysema from chest X-rays remains challenging due to imbalanced data, image noise, and the limitations of traditional deep networks in managing diagnostic uncertainty. In ...