Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Abstract: This paper presents LYRICEL, a framework integrating Knowledge Graph (KG) representation learning, Large Language Models (LLMs), and machine learning for reliable, explainable, and ...
Abstract: Network Intrusion Detection Systems (NIDS) are widely used to secure modern networks, but deploying accurate and scalable Machine Learning (ML)-based detection in high-speed environments ...
Conclusions: We developed a machine learning model for delirium prediction in ICU patients using routinely measured variables, including physiological waveforms. Our study demonstrates the potential ...
Early identification and prediction of persistent SA-AKI are crucial. Objective: The aim of this study was to develop and validate an interpretable machine learning (ML) model that predicts persistent ...
Background: Diabetic foot ulcer (DFU) is a common and serious complication in patients with diabetes, which affects the quality of life greatly as well as brings high risk for mortality.
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