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Validation of lactate and glucose in cerebrospinal fluid (CSF) on a Radiometer blood gas analyzer ABL90 Flex plus.
Clin Biochem
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Pathology and Laboratory Medicine Program, Health Sciences Centre, St. John's, Newfoundland and Labrador, Canada; Memorial University of Newfoundland, Health Sciences Centre, St. John's, Newfoundland and Labrador, Canada. Electronic address:
Purpose: Rapid determination of cerebrospinal fluid. (CSF) glucose and lactate is required by emergency rooms and intensive care units. Long turnaround time (TAT) on test results negatively impacts timely diagnosis and treatment of neurological infections like meningitis.
View Article and Find Full Text PDFTIMAR: Transition-informed representation for sample-efficient multi-agent reinforcement learning.
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CAS Key Laboratory of GIPAS, University of Science and Technology of China, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China. Electronic address:
In MARL (Multi-Agent Reinforcement Learning), the trial-and-error learning paradigm based on multiple agents requires massive interactions to produce training samples, significantly increasing both the training cost and difficulty. Therefore, enhancing data efficiency is a core issue in MARL. However, in the context of MARL, agent partially observed information leads to a lack of consideration for agent interactions and coordination from an ego perspective under the world model, which becomes the main obstacle to improving the data efficiency of current proposed MARL methods.
View Article and Find Full Text PDFValidation of AI-driven measurements for hip morphology assessment.
Eur J Radiol
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Department of Radiology, VA Boston Healthcare System, Boston University School of Medicine, Boston, MA, USA.
Rationale And Objectives: Accurate assessment of hip morphology is crucial for the diagnosis and management of hip pathologies. Traditional manual measurements are prone to mistakes and inter- and intra-reader variability. Artificial intelligence (AI) could mitigate such issues by providing accurate and reproducible measurements.
View Article and Find Full Text PDFForecasting O and NO concentrations with spatiotemporally continuous coverage in southeastern China using a Machine learning approach.
Environ Int
January 2025
School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China. Electronic address:
Ozone (O) is a significant contributor to air pollution and the main constituent ofphotochemical smog that plagues China. Nitrogen dioxide (NO) is a significant air pollutant and a critical trace gas in the Earth's atmosphere. The presence of O and NO has detrimental effects on human health, the ecosystem, and agricultural production.
View Article and Find Full Text PDFEnhancing meteorological data reliability: An explainable deep learning method for anomaly detection.
J Environ Manage
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Shaanxi Atmospheric Observation Technical Support Center, Xi'an, 710000, China. Electronic address:
Accurate meteorological observation data is of great importance to human production activities. Meteorological observation systems have been advancing toward automation, intelligence, and informatization. Yet, instrumental malfunctions and unstable sensor node resources could cause significant deviations of data from the actual characteristics it should reflect.
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