This study aimed to develop an interpretable machine learning model for predicting in-hospital mortality among acute ischemic stroke (AIS) patients admitted to the intensive care unit (ICU) using only routine clinical variables, without requiring Nat... read more
BACKGROUD: No universally accepted model exists for predicting bleeding risk in patients receiving low-molecular-weight heparin or fondaparinux. OBJECTIVE: This study leveraged seven machine learning algorithms to build a short-term bleeding risk p... read more
This study focuses on the fabrication and analysis of hybrid epoxy based composites using jute fiber (JF) and Linz-Donawitz (LD) sludge as reinforcement materials. The composites were fabricated through a hand-lay-up technique, with LD sludge concent... read more
Frequent shallow loess disasters pose severe threats to line engineering and public safety. Millimeter-scale cracks serve as key controlling factors in the initial stage of shallow loess disaster development. Such cracks can alter the morphology and ... read more
The complex ocean disturbances in ocean engineering have long constrained the precise autonomous navigation of intelligent marine vehicles, such as surface vessels and underwater vehicles. Nevertheless, the unpredictable wind-wave-current coupling ef... read more
This study develops and evaluates a data-leak-safe, monthly forecasting framework for the City of Ekurhuleni, South Africa, covering rainfall and municipal water demand. Here "leak-safe" means that all predictors are built from information that would... read more
Molecular mediators have demonstrated broad applicability in electrolyte chemistry of lithium-sulfur batteries, transforming sulfur conversion from traditional multiphase reactions to highly reactive pathways1-6. Despite tremendous efforts to elucida... read more
Multicellular programs in the tumour microenvironment (TME) drive cancer pathogenesis and response to therapy but remain challenging to identify and profile clinically1-3. Here, we present a machine-learning framework for multi-analyte profiling of s... read more
The malicious URLs have been a constant threat to cybersecurity because hackers are constantly creating phishing, malware, spam, and defacement links that resemble authentic Web layouts and bypass static security measures. Despite very promising resu... read more
The increasing complexity of natural language reasoning in artificial intelligence necessitates a shift from opaque, black-box processing to transparent, interpretable decision-making. While large language models (LLMs) demonstrate remarkable generat... read more
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