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IEEE International Symposium on Biomedical Imaging

作者： Qinghao Liang Brendan D. Adkinson Dustin Scheinost Department of Biomedical Engineering Yale University New Haven CT Interdepartmental Neuroscience Program Yale University New Haven CT Department of Radiology and Biomedical Imaging Yale School of Medicine New Haven CT Department of Statistics and Data Science Yale University New Haven CT

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Leveraging large-scale neuroimaging datasets to improve predictive modeling in smaller, specialized cohorts is essential for translating research findings into clinical applications. To address this challenge, we propose a meta-learning inspired approach that enhances phenotype prediction by exploiting inter-phenotype correlations across independent datasets, without requiring uniform imaging data processing. By employing mappings derived from a small, independent cohort with data processed using different atlases, we align the data in the meta-training set to the target space of the meta-testing set. This approach eliminates the need for extensive data reprocessing. Evaluation in the UK Biobank dataset shows that our framework significantly improves predictive performance on unseen phenotypes, demonstrating its potential to generalize connectome-based models to small, heterogeneous cohorts.

关键词： Metalearning Neuroimaging Phenotypes Correlation Biological system modeling Predictive models data processing Biomedical imaging

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On the particle approximation of lagged Feynman–Kac formulae

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Stochastic Processes and their Applications 2025年 188卷

作者： Awadelkarim, Elsiddig Caffarel, Michel Del Moral, Pierre Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal 23955-6900 Saudi Arabia University of Toulouse CNRS-Lab. de Chimie et Physique Quantiques Toulouse 31062 France Centre de Recherche Inria Bordeaux Sud-Ouest Talence 33405 France School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China

In this paper we examine the numerical approximation of the limiting invariant measure associated with Feynman–Kac formulae. These are expressed in a discrete time formulation and are associated with a Markov chain and a potential function. The typical application considered here is the computation of eigenvalues associated with non-negative operators as found, for example, in physics or particle simulation of rare-events. We focus on a novel lagged approximation of this invariant measure, based upon the introduction of a ratio of time-averaged Feynman–Kac marginals associated with a positive operator iterated l∈N times;a lagged Feynman–Kac formula. This estimator and its approximation using Diffusion Monte Carlo (DMC) are commonly used in the physics literature. In short, DMC is an iterative algorithm involving N∈N particles or walkers simulated in parallel, that undergo sampling and resampling operations. In this work, it is shown that for the DMC approximation of the lagged Feynman–Kac formula, one has an almost sure characterization of the L₁-error as the time parameter (iteration) goes to infinity and this is at most of O(exp{−κl}/N), for κ>0. In addition a non-asymptotic in time, and time uniform L₁−bound is proved which is O(l/N). We also prove a novel central limit theorem to give a characterization of the exact asymptotic in time variance. This analysis demonstrates that the strategy used in physics, namely, to run DMC with N and l small and, for long time enough, is mathematically justified. Our results also suggest how one should choose N and l in practice. We emphasize that these results are not restricted to physical applications;they have broad relevance to the general problem of particle simulation of the Feynman–Kac formula, which is utilized in a great variety of scientific and engineering fields. © 2025 Elsevier B.V.

关键词： Diffusion Monte Carlo Eigenvalue approximation Feynman–Kac formula

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Development of location suitability prediction for health facilities using random forest machine learning in 2030 integrating remote sensing and GIS in West Java, Indonesia

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Environmental Advances 2025年 19卷

作者： Virtriana, Riantini Ihsan, Kalingga Titon Nur Anggraini, Tania Septi Deliar, Albertus Harto, Agung Budi Riqqi, Akhmad Sakti, Anjar Dimara Remote Sensing and GIS Research Group Faculty of Earth Science and Technology Bandung Institute of Technology Bandung 40132 Indonesia Center for Remote Sensing Bandung Institute of Technology Bandung 40132 Indonesia Doctor Program in Program Study of Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung 40132 Indonesia Geographic Information Science Universitas Pendidikan Indonesia Bandung 40111 Indonesia Center for Spatial Data Infrastructure Bandung Institute of Technology Bandung 40132 Indonesia

Access to healthcare facilities is crucial in the present day. Healthcare facilities must be proportional to the population in a given area. Therefore, it is important to increase the number of healthcare facilities in regions where there is an imbalance. Proper planning and a sustainability review are necessary when determining locations for healthcare facilities. Environmental changes can affect the suitability of a location in the future. Thus, planning that can predict future suitability conditions is required to ensure that the built locations have high sustainability. This study predicts the suitability of healthcare facility locations in 2030 in West Java using remote sensing and Geographic Information System (GIS). Both static and dynamic data processed at 30×30 meter intervals across West Java will be used. Geospatial and remote sensing data are utilized in the study. Dynamic parameter extrapolation uses data from 2000 to 2018. The random forest machine learning method is employed to obtain the suitability values for healthcare facility locations using existing health facility training data in West Java. The results show changes in the suitability classes of healthcare facilities in each region from 2018 to 2030, with some areas experiencing an increase or decrease in class. This research highlights consistently suitable locations, ensuring their sustainability as healthcare facility sites. © 2024

关键词： GIS Health Facility Machine Learning Remote Sensing

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A multi-layered defense against adversarial attacks in brain tumor classification using ensemble adversarial training and feature squeezing

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Scientific Reports 2025年第1期15卷 1-11页

作者： Yinusa, Ahmeed Faezipour, Misa Computational and Data Science Program Middle Tennessee State University 1301 East Main Street Murfreesboro 37132 TN United States Department of Engineering Technology Middle Tennessee State University 1301 East Main Street Murfreesboro 37132 TN United States

Deep learning, particularly convolutional neural networks (CNNs), has proven valuable for brain tumor classification, aiding diagnostic and therapeutic decisions in medical imaging. Despite their accuracy, these models are vulnerable to adversarial attacks, compromising their reliability in clinical settings. In this research, we utilized a VGG16-based CNN model to classify brain tumors, achieving 96% accuracy on clean magnetic resonance imaging (MRI) data. To assess robustness, we exposed the model to Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD) attacks, which reduced accuracy to 32% and 13%, respectively. We then applied a multi-layered defense strategy, including adversarial training with FGSM and PGD examples and feature squeezing techniques such as bit-depth reduction and Gaussian blurring. This approach improved model resilience, achieving 54% accuracy on FGSM and 47% on PGD adversarial examples. Our results highlight the importance of proactive defense strategies for maintaining the reliability of AI in medical imaging under adversarial conditions. © The Author(s) 2025.

关键词： Adversarial attacks Adversarial training Artificial intelligence (AI) Brain tumor Feature squeezing Magnetic resonance imaging (MRI)

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Hospital Transfers for Hip Fracture Patients Are Associated With Higher Cost and Mortality

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Journal of Arthroplasty 2025年

作者： Hutchison, Catherine E.T. Rollier, Genevieve Li, Hsin-Fang Wells, Erica Workman, Kimberly L. Duwelius, Paul J. Lieberman, Elizabeth G. Oregon Health & Science University Department of Orthopaedics and Rehabilitation Portland Oregon United States Providence St. Joseph Health Surgery & Orthopedic Program Portland Oregon United States Providence St. Joseph Health Center for Cardiovascular Analytics Research & Data Science (CARDS) Portland Oregon United States Orthopedic and Fracture Specialists Portland Oregon United States

Background: Transferring hip fracture patients may increase morbidity and cost. The purpose of this study was to examine time to surgery, outcomes, and cost in patients undergoing operative management of displaced femoral neck fractures (DFNFs), comparing those admitted through the emergency department (ED) and those transferred from outside hospitals. Methods: A retrospective review of surgically managed DFNF patients (age ≥ 65 years) at a single institution between May 29, 2020, and December 29, 2022, was performed. Patients were categorized into two groups: “ED arrivals” and “transfers.” Demographics, time from presentation to surgery, hospital length of stay, discharge disposition, 1-year readmission, reoperation, and mortality, and total cost of care were collected and compared. We identified 459 patients (ED = 422, 92.0%, Transfer = 37, 8.0%). There was no difference in age, sex, body mass index, or American Society of Anesthesiologists status. Results: Median time from ED to operating room was higher in the transfer group (41.6 versus 23.2 hours, P < 0.0001). Transfer and ED patients had similar length of stay (5.9 versus 6.0 days, P = 0.29) and similar rates of discharge to skilled nursing facility (66.1 versus 62.2%, P = 0.39). There was a higher rate of 1-year mortality (27.0 versus 13.5% for ED, P = 0.03) in transfer patients but no difference in 1-year readmission or reoperation. Adjusting for demographics, transfer patients had 2.6 higher odds of 1-year mortality than ED patients (odds ratio = 2.59 (1.13 to 5.94) P = 0.03). The cost of care was higher for transfer patients ($23,521 versus $13,980, P < 0.0001). Conclusions: Transferring DFNF patients was associated with delayed time to surgery, increased 1-year mortality, and higher costs. Transferring patients is a logistical reality for many conditions;however, efforts should be made to provide efficient, safe, and cost-effective care. © 2025 Elsevier Inc.

关键词： femoral neck fracture geriatric fracture health care costs hip fracture transfer of care

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Variational Transformer Ansatz for the Density Operator of Steady States in Dissipative Quantum Many-Body Systems

arXiv

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arXiv 2025年

作者： Wei, Lu Jia, Zhian Wang, Yufeng Kaszlikowski, Dagomir Ling, Haibin Department of Applied Mathematics & Statistics Stony Brook University Stony BrookNY11794 United States Program of Data Science Stony Brook University Stony BrookNY11794 United States Centre for Quantum Technologies National University of Singapore SG 117543 Singapore Department of Physics National University of Singapore SG 117543 Singapore Department of Computer Science Stony Brook University Stony BrookNY11794 United States

The transformer architecture, known for capturing long-range dependencies and intricate patterns, has extended beyond natural language processing. Recently, it has attracted significant attention in quantum information and condensed matter physics. In this work, we propose the transformer density operator ansatz for determining the steady states of dissipative quantum many-body systems. By vectorizing the density operator as a many-body state in a doubled Hilbert space, the transformer encodes the amplitude and phase of the state’s coefficients, with its parameters serving as variational variables. Our design preserves translation invariance while leveraging attention mechanisms to capture diverse long-range correlations. We demonstrate the effectiveness of our approach by numerically calculating the steady states of dissipative Ising and Heisenberg spin chain models, showing that our method achieves excellent accuracy in predicting steady states. © 2025, CC BY.

关键词： Hilbert spaces

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Endemism shapes viral ecology and evolution in globally distributed hydrothermal vent ecosystems

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Nature Communications 2025年第1期16卷 1-14页

作者： Langwig, Marguerite V. Koester, Faith Martin, Cody Zhou, Zhichao Joye, Samantha B. Reysenbach, Anna-Louise Anantharaman, Karthik Department of Bacteriology University of Wisconsin-Madison Madison WI United States Freshwater and Marine Sciences Program University of Wisconsin-Madison Madison WI United States Microbiology Doctoral Training Program University of Wisconsin-Madison Madison WI United States Department of Marine Sciences University of Georgia Athens GA United States Department of Biology Portland State University Portland OR United States Department of Integrative Biology University of Wisconsin-Madison Madison WI United States Department of Data Science and AI Wadhwani School of Data Science and AI Indian Institute of Technology Madras TN Chennai India

Viruses are ubiquitous in deep-sea hydrothermal vents, where they influence microbial communities and biogeochemistry. Yet, viral ecology and evolution remain understudied in these environments. Here, we identify 49,962 viruses from 52 globally distributed hydrothermal vent samples (10 plume, 40 deposit, and 2 diffuse flow metagenomes), and reconstruct 5708 viral metagenome-assembled genomes, the majority of which were bacteriophages. Hydrothermal viruses were largely endemic, however, some viruses were shared between geographically separated vents, predominantly between the Lau Basin and Brothers Volcano in the Pacific Ocean. Geographically distant viruses shared proteins related to core functions such as structural proteins, and rarely, proteins of auxiliary functions involved in processes such as fermentation and cobalamin biosynthesis. Common microbial hosts of viruses included members of Campylobacterota, Alpha-, and Gammaproteobacteria in deposits, and Gammaproteobacteria in plumes. Campylobacterota- and Gammaproteobacteria-infecting viruses reflected variations in hydrothermal chemistry and functional redundancy in their predicted microbial hosts, suggesting that hydrothermal geology is a driver of viral ecology and coevolution of viruses and hosts. Our results indicate that viral ecology and evolution in globally distributed hydrothermal vents is shaped by endemism and thus may have increased susceptibility to the negative impacts of deep-sea mining and anthropogenic change in ocean ecosystems. © The Author(s) 2025.

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In silico prediction of loop-mediated isothermal amplification using a generalized linear model

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Synthetic Biology 2025年第1期10卷

作者： Taguchi, Kenshiro Michiyuki, Satoru Tsuji, Takumasa Kotoku, Jun’ichi Graduate Degree Program of Health Data Science Teikyo University 2-11-1 Kaga Itabashi-Ku Tokyo173-8605 Japan Fundamental Research Laboratory Eiken Chemical Co. Ltd Tochigi329-0114 Japan Graduate School of Medical Care and Technology Teikyo University 2-11-1 Kaga Itabashi-Ku Tokyo173-8605 Japan

Loop-mediated isothermal amplification (LAMP), a DNA amplification technique under isothermal conditions, provides the important benefits of high sensitivity, specificity, rapidity, and simplicity. Maximizing LAMP features necessitates the design of a complex LAMP primer set (LPS) consisting of four primers for six regions of a given target DNA. Furthermore, the LPS of a given target DNA is designed with LPS design support software such as Primer Explorer. However, even if the design is completed, we still must do many in vitro experiments and evaluations. Consequently, designing LPS often fails to achieve high performance, including efficient amplification. For this study, we examined in silico LAMP: a generalized linear model to predict DNA amplification from LPS. Using logistic regression with elastic net regularization, we identified factors that strongly affect LPS design. These factors, combined with domain knowledge for LPS design, led to the creation of LAMP kernel variables that are highly essential for high LAMP reaction. In silico LAMP, constructed using logistic regression with LAMP kernel variables, allows classification and performance prediction of LPS with an area under the curve of 0.86. These results suggest that a high LAMP reaction can be predicted using LAMP kernel variables and generalized linear regression model. Moreover, an LPS with high performance can be constructed without in vitro experimentation. © The Author(s) 2025. Published by Oxford University Press.

关键词： Logistic regression

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Genetic keys to microbial gut colonization

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Cell host & microbe 2025年第5期33卷 605-607页

作者： Karthik Anantharaman Cody Martin Department of Bacteriology University of Wisconsin-Madison Madison WI USA Department of Integrative Biology University of Wisconsin-Madison Madison WI USA Department of Data Science and AI Indian Institute of Technology Madras Chennai TN India. Electronic address: karthik@bact.wisc.edu. Microbiology Doctoral Training Program University of Wisconsin-Madison Madison WI USA.

What enables certain microbes to successfully colonize the mammalian gut? In a recent issue of Cell, Liu et al. present a microbial cross-species genomic framework that identifies conserved genetic determinants of gut residency. This study provides a roadmap for developing more effective microbiome-based therapeutics, advancing our understanding of host-microbe interactions.

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Method for modelling the number of HIV and AIDS cases using least square spline Biresponse nonparametric negative binomial regression

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MethodsX 2025年 14卷 103336页

作者： Ramadan, Arip Chamidah, Nur Budiantara, I Nyoman Lestari, Budi Aydin, Dursun Doctoral Study Program of Mathematics and Natural Sciences Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Information System Study Program Department of Industrial and System Engineering Telkom University Surabaya Campus Surabaya 60231 Indonesia Department of Mathematics Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Research Group of Statistical Modeling in Life Science Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Statistics Department Faculty of Science and Data Analytics Sepuluh Nopember Institute of Technology Surabaya 60111 Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences The University of Jember Jember 68121 Indonesia Department of Statistics Faculty of Science Muğla Sıtkı Koçman University Muğla 48000 Turkey Research Scholar at Department of Mathematics University of Wisconsin Oshkosh Algoma Blvd Oshkosh 54901 WI United States

We propose a new statistical modeling method to analyze functional relationship between predictor variables and correlated response variables, and apply it for modeling the number of HIV and AIDS cases influenced by early-age marriages and contraceptive users. The proposed method is LS-Spline BNNBR that is a Biresponse Nonparametric Negative Binomial Regression (BNNBR) based on least squares spline (LS-Spline). To validate the proposed method, we compare it with classical method, namely Ordinary Least Square Biresponse Parametric Negative Binomial Regression (OLS-BPNBR). The results show that the LS-Spline BNNBR method provided deviance value of 7.542334 which is smaller than that of OLS-BPNBR method, namely 7.993935. Thus, the proposed method has better prediction fit than the classical method. • This study discusses new statistical modeling method for the number of HIV and AIDS cases influenced by early-age marriages and contraceptive users where the response variables are correlated with each other. • The model estimation results show that the number of HIV and AIDS cases in Indonesia will decrease if the early-age marriages percentage increases and the contraceptive users percentage decreases. • The results are useful to provide a scientific basis for making policies to control the number of HIV and AIDS cases in Indonesia. © 2025 The Authors

关键词： AIDS BLSSNNBR model Contraceptive user Early-age marriage HIV Least square spline

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