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CODE-ACCORD: A Corpus of building regulatory data for rule generation towards automatic compliance checking.
Sci Data
January 2025
Faculty of Computing, Engineering and Built Environment, Birmingham City University, Birmingham, B4 7XG, UK.
Automatic Compliance Checking (ACC) within the Architecture, Engineering, and Construction (AEC) sector necessitates automating the interpretation of building regulations to achieve its full potential. Converting textual rules into machine-readable formats is challenging due to the complexities of natural language and the scarcity of resources for advanced Machine Learning (ML). Addressing these challenges, we introduce CODE-ACCORD, a dataset of 862 sentences from the building regulations of England and Finland.
View Article and Find Full Text PDFHilbert transform analysis of the mouse scotopic electroretinogram reveals two distinct bursts of oscillatory potentials with progressively dimmer flashes.
Doc Ophthalmol
January 2025
Department of Ophthalmology and Visual Sciences, Research Institute of the McGill University Health Centre/Montreal Children's Hospital, 1001 Décarie Boulevard, Glen Site, Block E, Office #EM03238, Montréal, QC, H4A 3J1, Canada.
Purpose: Study the scotopic oscillatory potentials (OPs) in mice over a wide range of flash luminance levels using the Hilbert transform (HT) to extract new features of the high frequency components of the electroretinogram (ERG).
Methods: Scotopic ERGs [Intensity: - 6.3 to 0.
Using partially shared radiomics features to simultaneously identify isocitrate dehydrogenase mutation status and epilepsy in glioma patients from MRI images.
Sci Rep
January 2025
Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China.
Prediction of isocitrate dehydrogenase (IDH) mutation status and epilepsy occurrence are important to glioma patients. Although machine learning models have been constructed for both issues, the correlation between them has not been explored. Our study aimed to exploit this correlation to improve the performance of both of the IDH mutation status identification and epilepsy diagnosis models in patients with glioma II-IV.
View Article and Find Full Text PDFVAE-Surv: A novel approach for genetic-based clustering and prognosis prediction in myelodysplastic syndromes.
Comput Methods Programs Biomed
January 2025
Computational Biomedicine Unit, Department of Medical Sciences, University of Torino, Via Santena 19, 10126, Torino, Italy.
Background And Objectives: Several computational pipelines for biomedical data have been proposed to stratify patients and to predict their prognosis through survival analysis. However, these analyses are usually performed independently, without integrating the information derived from each of them. Clustering of survival data is an underexplored problem, and current approaches are limited for biomedical applications, whose data are usually heterogeneous and multimodal, with poor scalability for high-dimensionality.
View Article and Find Full Text PDFExplainable vision transformer for automatic visual sleep staging on multimodal PSG signals.
NPJ Digit Med
January 2025
Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea.
Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by the 'black-box' nature. In this study, we present SleepXViT, an automatic sleep staging system using Vision Transformer (ViT) that provides intuitive, consistent explanations by mimicking human 'visual scoring'.
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