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Characteristics and outcomes of out-of-hospital cardiac arrest among students under school supervision in Japan: a descriptive epidemiological study (2008-2021).
Environ Health Prev Med
January 2025
Division of Environmental Medicine and Population Sciences, Department of Social and Environmental Medicine, Graduate School of Medicine, Osaka University.
Background: A comprehensive understanding of the epidemiology of pediatric out-of-hospital cardiac arrest (OHCA) occurring under school supervision is lacking. We aimed to comprehensively describe the characteristics and outcomes of OHCA among students in elementary schools, junior high schools, high schools, and technical colleges in Japan.
Methods: OHCA data from 2008-2021 were obtained from the SPIRITS study, which provides a nationwide database of OHCAs occurring under school supervision across Japan.
4.5-Year Follow-up with a Novel Corneal Endothelial Prosthesis.
Klin Monbl Augenheilkd
January 2025
Ophthalmology, Amsterdam UMC, Amsterdam, Netherlands.
Background: Refractory corneal edema is the foremost reason for endothelial corneal transplantation (EK) in the world. Descemet membrane endothelial keratoplasty (DMEK) and Descemet stripping automated endothelial keratoplasty (DSAEK) offer good clinical outcomes. However, human donor tissue is limited in availability and has a complex logistical chain.
View Article and Find Full Text PDFEnrichRBP: an automated and interpretable computational platform for predicting and analyzing RNA-binding protein events.
Bioinformatics
January 2025
School of Artificial Intelligence, Jilin University, Jilin, China.
Motivation: Predicting RNA-binding proteins (RBPs) is central to understanding post-transcriptional regulatory mechanisms. Here, we introduce EnrichRBP, an automated and interpretable computational platform specifically designed for the comprehensive analysis of RBP interactions with RNA.
Results: EnrichRBP is a web service that enables researchers to develop original deep learning and machine learning architectures to explore the complex dynamics of RNA-binding proteins.
Artificial intelligence-enabled safety monitoring in Alzheimer's disease clinical trials.
J Prev Alzheimers Dis
January 2025
Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, United States.
Background: Investigators conducting clinical trials have an ethical, scientific, and regulatory obligation to protect the safety of trial participants. Traditionally, safety monitoring includes manual review and coding of adverse event data by expert clinicians.
Objectives: Our study explores the use of natural language processing (NLP) and artificial intelligence (AI) methods to streamline and standardize clinician coding of adverse event data in Alzheimer's disease (AD) clinical trials.
Interpretable flash flood susceptibility mapping in Yarlung Tsangpo River Basin using H2O Auto-ML.
Sci Rep
January 2025
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Beijing, 100101, China.
Flash flood susceptibility mapping is essential for identifying areas prone to flooding events and aiding decision-makers in formulating effective prevention measures. This study aims to evaluate the flash flood susceptibility in the Yarlung Tsangpo River Basin (YTRB) using multiple machine learning (ML) models facilitated by the H2O automated ML platform. The best-performing model was used to generate a flash flood susceptibility map, and its interpretability was analyzed using the Shapley Additive Explanations (SHAP) tree interpretation method.
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