High-speed train operation data are reliable and rich resources in data-driven research. However, the data released by railway companies are poorly organized and not comprehensive enough to be applied directly and effectively. A public high-speed railway network dataset suitable for research is still lacking. To support the research in large-scale complex network, complex dynamic system and intelligent transportation, we develop a high-speed railway network dataset, containing the train operation data in different directions from October 8, 2019 to January 27, 2020, the train delay data of the railway stations, the junction stations data, and the mileage data of adjacent stations. In the dataset, weather, temperature, wind power and major holidays are considered as factors affecting train operation. Potential research values of the dataset include but are not limited to complex dynamic system pattern mining, community detection and discovery, and train delay analysis. Besides, the dataset can be used to solve various railway operation and management problems, such as passenger service network improvement, train real-time dispatching and intelligent driving assistance.
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http://dx.doi.org/10.1038/s41597-022-01349-8 | DOI Listing |
Int J Comput Assist Radiol Surg
January 2025
Medical Informatics, University of Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.
Purpose: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for segmentation, it falls short in landmark detection, a strength of shape-based approaches.
Methods: In this work, we propose a dense image-to-shape representation that enables the joint learning of landmarks and semantic segmentation by employing a fully convolutional architecture.
Eur J Pediatr
January 2025
Global Health and Tropical Medicine, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, Lisbon, Portugal.
Purpose: Under-five mortality is a key public health indicator, highly responsive to preventive interventions. While global efforts have made strides in reducing mortality rates in this age group, significant disparities persist, particularly in Sub-Saharan Africa. This study aimed to systematically review the factors influencing under-five mortality in Africa, focusing on sociodemographic factors and health-related determinants.
View Article and Find Full Text PDFNeurosurg Rev
January 2025
Department of Neurosurgery, Mount Sinai Hospital, Icahn School of Medicine, New York City, NY, USA.
Currently, the World Health Organization (WHO) grade of meningiomas is determined based on the biopsy results. Therefore, accurate non-invasive preoperative grading could significantly improve treatment planning and patient outcomes. Considering recent advances in machine learning (ML) and deep learning (DL), this meta-analysis aimed to evaluate the performance of these models in predicting the WHO meningioma grade using imaging data.
View Article and Find Full Text PDFDiabetologia
January 2025
MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Aims/hypothesis: UK standard care for type 2 diabetes is structured diabetes education, with no effects on HbA, small, short-term effects on weight and low uptake. We evaluated whether remotely delivered tailored diabetes education combined with commercial behavioural weight management is cost-effective compared with current standard care in helping people with type 2 diabetes to lower their blood glucose, lose weight, achieve remission and improve cardiovascular risk factors.
Methods: We conducted a pragmatic, randomised, parallel two-group trial.
Curr Diab Rep
January 2025
Centre for Surveillance and Applied Research, Health Promotion and Chronic Disease Prevention Branch, Public Health Agency of Canada, 785 Carling Ave, Ottawa, Ontario, K1A 0K9, Canada.
Purpose Of Review: The prevalence of diabetes is rising around the world and represents an important public health concern. Unlike individual-level risk and protective factors related to the etiology of diabetes, contextual risk factors have been much less studied. Identification of contextual factors related to the risk of type 1 and type 2 diabetes in Organisation for Economic Co-operation and Development (OECD) countries may help health professionals, researchers, and policymakers to improve surveillance, develop policies and programs, and allocate funding.
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