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arXiv 2025年

作者： Riley, Richard D. Whittle, Rebecca Sadatsafavi, Mohsen Martin, Glen P. Pate, Alexander Collins, Gary S. Ensor, Joie Department of Applied Health Sciences School of Health Sciences College of Medicine and Health University of Birmingham Birmingham United Kingdom Birmingham Biomedical Research Centre United Kingdom Respiratory Evaluation Sciences Program Faculty of Pharmaceutical Sciences The University of British Columbia Vancouver Canada Division of Informatics Imaging and Data Science Faculty of Biology Medicine and Health University of Manchester Manchester Academic Health Science Centre Manchester United Kingdom Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford OxfordOX3 7LD United Kingdom

Background Existing sample size calculations for developing clinical prediction models rely on standard (unpenalised) regression-based formula. A general approach is needed for developing or updating a CPM using any statistical or machine learning method. Objectives To propose a general framework for sample size calculations applicable to any model development approach, based on drawing samples from anticipated sampling/posterior distributions and targeting minimal degradation in predictive performance compared to reference model. Methods Researchers must provide candidate predictors, their reference model (e.g., a regression equation matching outcome incidence, predictor weights and c-statistic of previous models), and a (synthetic) dataset reflecting the joint distribution of candidate predictors in the target population. Then, a fully simulation-based approach allows the impact of a chosen development sample size and modelling strategy to be examined. This generates thousands of models and, by applying each to the entire target population, leads to sampling/posterior distributions of individual predictions and model performance (degradation) metrics, to inform required sample sizes. To improve computational speed for penalised regression, we also propose a one-sample Bayesian analysis that combines shrinkage priors with a likelihood decomposed into sample size and Fisher’s unit information. Results The framework is illustrated when developing pre-eclampsia prediction models using logistic regression (unpenalised, uniform shrinkage, lasso or ridge) and random forests. It encompasses existing sample size calculation criteria whilst also providing model assurance probabilities, instability metrics, and degradation statistics about calibration, discrimination, clinical utility, prediction error and fairness. Crucially, the required sample size depends on the users’ key estimands of interest and planned model development or updating approach. Conclusions The new, flex

关键词： Size distribution

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TITLE: Examining Online Social Support for Countering QAnon Conspiracies

arXiv

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arXiv 2025年

作者： Haupt, Michael Robert Larsen, Meng Zhen Strayer, Michelle Yang, Luning Mackey, Tim K. Department of Cognitive Science University of California 9500 Gilman Dr La Jolla San DiegoCA92093 United States Global Health Program Department of Anthropology University of California San DiegoCA United States Global Health Policy & Data Institute San DiegoCA United States Columbia University New YorkNY United States S-3 Research San DiegoCA United States

As radical messaging has proliferated on social networking sites, platforms like Reddit have been used to host support groups, including support communities for the families and friends of radicalized individuals. This study examines the subreddit r/QAnonCasualties, an online forum for users whose loved ones have been radicalized by QAnon. We collected 1,665 posts and 78,171 comments posted between 7/2021 and 7/2022 and content coded top posts for prominent themes. Sentiment analysis was also conducted on all posts. We find venting, advice and validation-seeking, and pressure to refuse the COVID-19 vaccine were prominent themes. 40% (n=167) of coded posts identified the user’s Q relation(s) as their parent(s) and 16.3% (n=68) as their partner. Posts with higher proportions of words related to swearing, social referents, and physical needs were positively correlated with engagement. These findings show ways that communities around QAnon adherents leverage anonymous online spaces to seek and provide social support. © 2025, CC BY-NC-SA.

关键词： Social psychology

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Simplex path integral and simplex renormalization group for high-order interactions

arXiv

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arXiv 2023年

作者： Cheng, Aohua Xu, Yunhui Sun, Pei Tian, Yang Department of Psychology Tsinghua Laboratory of Brain and Intelligence Tsinghua University Beijing100084 China Tsien Excellence in Engineering Program Tsinghua University Beijing100084 China Department of Physics Tsinghua University Beijing100084 China Faculty of Health Sciences City University of Macau 999078 China Faculty of Data Science City University of Macau 999078 China

Modern theories of phase transitions and scale-invariance are rooted in path integral formulation and renormalization group (RG). Despite the applicability of these approaches on simple systems with only pairwise interactions, they are less effective on complex systems with un-decomposable high-order interactions (i.e., interactions among arbitrary sets of units). To precisely characterize the universality of high-order interacting systems, we propose simplex path integral and simplex renormalization group (SRG) as the generalizations of classic approaches to arbitrary high-order and heterogeneous interactions. We first formalize the trajectories of units governed by high-order interactions to define path integrals on corresponding simplices based on a high-order propagator. Then we develop a method to integrate out short-range high-order interactions in the momentum space, accompanied by a coarse graining procedure functioning on the simplex structure generated by high-order interactions. The proposed SRG, equipped with a divide-and-conquer framework, can deal with the absence of ergodicity arised from the sparse distribution of high-order interactions and renormalize a system with intertwined high-order interactions on the p-order according to its properties on the q-order (p ≤ q). The associated scaling relation and its corollaries support to differentiate among scale-invariant, weakly scale-invariant, and scale-dependent systems across different orders. We have validated our theory in multi-order scale-invariance verification, topological invariance discovery, organizational structure identification, and information bottleneck analysis. These experiments demonstrate the capacity of our theory for identifying intrinsic statistical and topological properties of high-order interacting systems during system reduction. © 2023, CC BY.

关键词： Topology

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Robust shape estimation with false-positive contact detection

arXiv

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arXiv 2021年

作者： Shibata, Kazuki Miyano, Tatsuya Jimbo, Tomohiko Matsubara, Takamitsu Autonomous Distributed Cooperative Control Program Data Analytics Research-Domain Toyota Central RandD Labs. Inc. 41-1 Yokomichi Nagakute Aichi Japan Graduate School of Science and Technology Division of Information Science Nara Institute of Science and Technology Nara Japan

We propose a means of omni-directional contact detection using accelerometers instead of tactile sensors for object shape estimation using touch. Unlike tactile sensors, our contact-based detection method tends to induce a degree of uncertainty with false-positive contact data because the sensors may react not only to actual contact but also to the unstable behavior of the robot. Therefore, it is crucial to consider a robust shape estimation method capable of handling such false-positive contact data. To realize this, we introduce the concept of heteroscedasticity into the contact data and propose a robust shape estimation algorithm based on Gaussian process implicit surfaces (GPIS). We confirmed that our algorithm not only reduces shape estimation errors caused by false-positive contact data but also distinguishes false-positive contact data more clearly than the GPIS through simulations and actual experiments using a quadcopter. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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Perturbation theory for evolution of cooperation on networks

arXiv

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arXiv 2022年

作者： Meng, Lingqi Masuda, Naoki Department of Mathematics University at Buffalo State University of New York BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

Network structure is a mechanism for promoting cooperation in social dilemma games. In the present study, we explore graph surgery, i.e., to slightly perturb the given network, towards a network that better fosters cooperation. To this end, we develop a perturbation theory to assess the change in the propensity of cooperation when we add or remove a single edge to/from the given network. Our perturbation theory is for a previously proposed random-walk-based theory that provides the threshold benefit-to-cost ratio, (b/c)∗, which is the value of the benefit-to-cost ratio in the donation game above which the cooperator is more likely to fixate than in a control case, for any finite networks. We find that (b/c)∗ decreases when we remove a single edge in a majority of cases and that our perturbation theory captures at a reasonable accuracy which edge removal makes (b/c)∗ small to facilitate cooperation. In contrast, (b/c)∗ tends to increase when we add an edge, and the perturbation theory is not good at predicting the edge addition that changes (b/c)∗ by a large amount. Our perturbation theory significantly reduces the computational complexity for calculating the outcome of graph *** Codes 91A22, 91D30 Copyright © 2022, The Authors. All rights reserved.

关键词： Surgery

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Synthetic Control Removes Spurious Discoveries from Double Dipping in Single-Cell and Spatial Transcriptomics data Analyses 29th

Synthetic Control Removes Spurious Discoveries from Double ...

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29th International Conference on Research in Computational Molecular Biology, RECOMB 2025

作者： Song, Dongyuan Chen, Siqi Lee, Christy Li, Kexin Ge, Xinzhou Li, Jingyi Jessica Department of Genetics and Genome Sciences University of Connecticut Health Center FarmingtonCT06032 United States Interdepartmental Program of Bioinformatics University of California Los Angeles Los AngelesCA90095-7246 United States Department of Statistics and Data Science University of California Los Angeles Los AngelesCA90095-1554 United States Department of Statistics Oregon State University CorvallisOR97331-4606 United States

ISBN: (纸本)9783031902512

Double dipping is a common analytical pitfall in single-cell and spatial transcriptomics data analysis: after a clustering algorithm finds clusters as putative cell types or spatial domains, statistical tests are applied to the same data to identify differentially expressed (DE) genes as potential cell-type or spatial-domain markers. Because the genes that contribute to clustering are inherently likely to be identified as DE genes, double dipping can result in false-positive markers, especially when clusters are spurious, leading to ambiguously defined cell types or spatial domains. To address this challenge, we propose ClusterDE, a statistical method designed to identify post-clustering DE genes as reliable markers of cell types and spatial domains, while controlling the false discovery rate (FDR) regardless of clustering quality. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Biomolecules

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Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine

arXiv

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arXiv 2024年

作者： Yang, Rui Ning, Yilin Keppo, Emilia Liu, Mingxuan Hong, Chuan Bitterman, Danielle S. Ong, Jasmine Chiat Ling Ting, Daniel Shu Wei Liu, Nan Center for Quantitative Medicine Duke-NUS Medical School Singapore Singapore Faculty of Arts and Science University of Toronto TorontoON Canada Department of Biostatistics and Bioinformatics Duke University DurhamNC United States Artificial Intelligence in Medicine Program Mass General Brigham Harvard Medical School BostonMA United States Division of Pharmacy Singapore General Hospital Singapore Singapore Singapore Eye Research Institute Singapore National Eye Center Singapore Singapore Byers Eye Institute Stanford University StanfordCA United States Program in Health Services and Systems Research Duke-NUS Medical School Singapore Singapore Institute of Data Science National University of Singapore Singapore Singapore

Generative artificial intelligence (AI) has brought revolutionary innovations in various fields, including medicine. However, it also exhibits limitations. In response, retrieval-augmented generation (RAG) provides a potential solution, enabling models to generate more accurate contents by leveraging the retrieval of external knowledge. With the rapid advancement of generative AI, RAG can pave the way for connecting this transformative technology with medical applications and is expected to bring innovations in equity, reliability, and personalization to health care. © 2024, CC BY.

关键词： Medical applications

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Whole slide images are 2D point clouds: Context-aware survival prediction using patch-based graph convolutional networks

arXiv

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arXiv 2021年

作者： Chen, Richard J. Lu, Ming Y. Shaban, Muhammad Chen, Chengkuan Chen, Tiffany Y. Williamson, Drew F.K. Mahmood, Faisal Department of Pathology Brigham and Women's Hospital Department of Biomedical Informatics Harvard Medical School Cancer Data Science Program Dana-Farber Cancer Institute Cancer Program Broad Institute of Harvard MIT

Cancer prognostication is a challenging task in computational pathology that requires context-aware representations of histology features to adequately infer patient survival. Despite the advancements made in weakly-supervised deep learning, many approaches are not context-aware and are unable to model important morphological feature interactions between cell identities and tissue types that are prognostic for patient survival. In this work, we present Patch-GCN, a context-aware, spatially-resolved patch-based graph convolutional network that hierarchically aggregates instance-level histology features to model local- and global-level topological structures in the tumor microenvironment. We validate Patch-GCN with 4,370 gigapixel WSIs across five different cancer types from the Cancer Genome Atlas (TCGA), and demonstrate that Patch-GCN outperforms all prior weakly-supervised approaches by 3.58-9.46%. Our code and corresponding models are publicly available at https://***/mahmoodlab/Patch-GCN. Copyright © 2021, The Authors. All rights reserved.

关键词： Pathology

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Correction to: Organic Matter DYnamic model (OMDY) predicts the wood debris decomposition of ten Mediterranean species

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Plant and Soil 2025年 1-2页

作者： Spigno, Sabrina Cartenì, Fabrizio Idbella, Mohamed Piscitelli, Alfonso Staiano, Michele Cangemi, Silvana Spaccini, Riccardo Mazzoleni, Stefano Bonanomi, Giuliano Giannino, Francesco Department of Agricultural Science University of Naples Federico II Portici Italy College of Agriculture and Environmental Sciences AgroBioSciences Program Mohammed VI Polytechnic University (UM6P) Ben Guerir Morocco Statistics Technology and Analysis of Data Department of Industrial Engineering University of Naples Federico II Naples Italy CERMANU-Centro Interdipartimentale di Ricerca sulla Risonanza Magnetica Nucleare per l’Ambiente l’Agro-Alimentare ed i Nuovi Materiali Portici Italy

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Comparison of endoscopic third ventriculostomy versus cerebrospinal fluid shunt procedures for the treatment of pediatric hydrocephalus in Taiwan

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Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery 2024年第9期40卷 2883-2891页

作者： Shu-Mei Chen Li-Ying Chen Jiann-Her Lin Nicole Salazar Tu-Hsueh Yeh Wei-Lun Lo Tai-Ngar Lui Yi-Chen Hsieh Li-Nien Chien Department of Neurosurgery Taipei Medical University Hospital Taipei Medical University Taipei Taiwan. Department of Surgery School of Medicine Taipei Medical University Taipei Taiwan. Health Data Analytics and Statistics Center Office of Data Science Taipei Medical University Taipei Taiwan. Julius L. Chambers Biomedical/Biotechnology Institute and Department of Biological & Biomedical Sciences North Carolina Central University Durham NC USA. Department of Neurology Taipei Medical University Hospital Taipei Taipei Medical University Taipei Taiwan. Department of Neurology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan. Department of Neurosurgery Shuang Ho Hospital Taipei Medical University Taipei Taiwan. The PhD Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University 250 Wu-Hsing Street Taipei Taiwan. ychsieh@tmu.edu.tw. Institute of Health and Welfare Policy College of Medicine National Yang Ming Chiao Tung University No.155 Sec. 2 Linong St. Beitou District Taipei Taiwan. linien.chien@nycu.edu.tw. Graduate Institute of Data Science College of Management Taipei Medical University Taipei Taiwan. linien.chien@nycu.edu.tw.

PURPOSE:Pediatric hydrocephalus is the most common cause of surgically treatable neurological disease in children. Controversies exist whether endoscopic third ventriculostomy (ETV) or cerebrospinal fluid (CSF) shunt placement is the most appropriate treatment for pediatric hydrocephalus. This study aimed to compare the risk of re-operation and death between the two procedures. METHODS:We performed a retrospective population-based cohort study and included patients younger than 20-years-old who underwent CSF shunt or ETV for hydrocephalus from the Taiwan National Health Insurance Research database. RESULTS:A total of 3,555 pediatric patients from 2004 to 2017 were selected, including 2,340 (65.8%) patients that received CSF shunt placement and 1215 (34.2%) patients that underwent ETV. The incidence of all-cause death was 3.31 per 100 person-year for CSF shunt group and 2.52 per 100 person-year for ETV group, with an adjusted hazard ratio (HR) of 0.79 (95% confidence interval [CI] = 0.66-0.94, p = 0.009). The cumulative incidence competing risk for reoperation was 31.2% for the CSF shunt group and 26.4% for the ETV group, with an adjusted subdistribution HR of 0.82 (95% CI = 0.70-0.96, p = 0.015). Subgroup analysis showed that ETV was beneficial for hydrocephalus coexisting with brain or spinal tumor, central nervous system infection, and intracranial hemorrhage. CONCLUSION:Our data indicates ETV is a better operative procedure for pediatric hydrocephalus when advanced surgical techniques and instruments are available.

关键词： Cerebrospinal shunt Pediatric hydrocephalus Reoperation Third ventriculostomy

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