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最新文章

• ONLINE MONITORING OF AIR QUALITY USING PCA-BASED SEQUENTIAL LEARNING AI翻译
  作者：Xie, Xiulin; Qian, Nicole; Qiu, Peihua
  作者单位：State University System of Florida; Florida State University; Northwestern University; State University System of Florida; University of Florida
  摘要：Air pollution surveillance is critically important for public health. One air pollutant, ozone, is extremely challenging to analyze properly, as it is a secondary pollutant caused by complex chemical reactions in the air and does not emit directly into the atmosphere. Numerous environmental studies confirm that ozone concentration levels are associated with meteorological conditions, and long-term exposure to high ozone concentration levels is associated with the incidence of many diseases, in...
• A NONSEPARABLE FIRST-ORDER SPATIOTEMPORAL INTENSITY FOR EVENTS ON LINEAR NETWORKS: AN APPLICATION TO AMBULANCE INTERVENTIONS AI翻译
  作者：Gilardi, Andrea; Borgoni, Riccardo; Mateu, Jorge
  作者单位：University of Milano-Bicocca; Universitat Jaume I
  摘要：The algorithms used for the optimal management of an ambulance fleet require an accurate description of the spatiotemporal evolution of the emergency events. In the last years, several authors have proposed sophisticated statistical approaches to forecast ambulance dispatches, typically modelling the data as a point pattern occurring on a planar region. Nevertheless, ambulance interventions can be more appropriately modelled as a realisation of a point process occurring on a linear network. Th...
• SELECTIVE INFERENCE FOR SPARSE MULTITASK REGRESSION WITH APPLICATIONS IN NEUROIMAGING AI翻译
  作者：Panigrahi, Snigdha; Stewart, Natasha; Sripada, Chandra; Levina, Elizaveta
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：Multitask learning is frequently used to model a set of related response variables from the same set of features, improving predictive performance and modeling accuracy relative to methods that handle each response variable separately. Despite the potential of multitask learning to yield more powerful inference than single-task alternatives, prior work in this area has largely omitted uncertainty quantification. Our focus in this paper is a common multitask problem in neuroimaging, where the g...
• ANOPOW FOR REPLICATED NONSTATIONARY TIME SERIES IN EXPERIMENTS AI翻译
  作者：Li, Zeda; Yue, Yu (ryan); Bruce, Scott A.
  作者单位：City University of New York (CUNY) System; Baruch College (CUNY); Texas A&M University System; Texas A&M University College Station
  摘要：We propose a novel analysis of power (ANOPOW) model for analyzing replicated nonstationary time series commonly encountered in experimental studies. Based on a locally stationary ANOPOW Cramer spectral representation, the proposed model can be used to compare the second -order timevarying frequency patterns among different groups of time series and to estimate group effects as functions of both time and frequency. Formulated in a Bayesian framework, independent two-dimensional second -order ra...
• DYNAMIC RISK PREDICTION FOR CERVICAL PRECANCER SCREENING WITH CONTINUOUS AND BINARY LONGITUDINAL BIOMARKERS AI翻译
  作者：Roy, Siddharth; Roy, Anindya; Clarke, Megan A.; Gradissimo, Ana; Burk, Robert D.; Wentzensen, Nicolas; Albert, Paul S.; Liu, Danping
  作者单位：National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics; University System of Maryland; University of Maryland Baltimore County; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics; Memorial Sloan Kettering Cancer Center; Montefiore Medical Center; Albert Einstein College of Medicine; Yeshiva University
  摘要：Dynamic risk prediction that incorporates longitudinal measurements of biomarkers is useful in identifying high-risk patients for better clinical management. Our work is motivated by the prediction of cervical precancers. Currently, Pap cytology is used to identify HPV-positive (HPV+) women at high-risk of cervical precancer, but cytology lacks accuracy and reproducibility. Molecular markers, like HPV DNA methylation, that are closely linked to the carcinogenic process show promise of improved...
• LAND-USE FILTERING FOR NONSTATIONARY SPATIAL PREDICTION OF COLLECTIVE EFFICACY IN AN URBAN ENVIRONMENT AI翻译
  作者：Carter, J. Brandon; Browning, Christopher R.; Boettner, Bethany; Pinchak, Nicolo; Calder, Catherine A.
  作者单位：University of Texas System; University of Texas Austin; University System of Ohio; Ohio State University; University System of Ohio; Ohio State University
  摘要：Collective efficacy-the capacity of communities to exert social control toward the realization of their shared goals-is a foundational concept in the urban sociology and neighborhood effects literature. Traditionally, empirical studies of collective efficacy use large sample surveys to estimate collective efficacy of different neighborhoods within an urban setting. Such studies have demonstrated an association between collective efficacy and local variation in community violence, educational a...
• NETWORK-LEVEL TRAFFIC FLOW PREDICTION: FUNCTIONAL TIME SERIES VS. FUNCTIONAL NEURAL NETWORK APPROACH AI翻译
  作者：Ma, Tao; Yao, Fang; Zhou, Zhou
  作者单位：Texas State University System; Texas State University San Marcos; Peking University; University of Toronto
  摘要：Traffic state prediction is an essential component and an underlying backbone of intelligent transportation systems, especially in the context of smart city framework. Its significance is mainly twofold in modern transportation systems: supporting advanced traffic operations and management for highways and urban road networks to mitigate traffic congestion and enabling individual drivers with connected vehicles in the traffic system to dynamically optimize their routes to improve travel time. ...
• COMPOSITE SCORES FOR TRANSPLANT CENTER EVALUATION: A NEW INDIVIDUALIZED EMPIRICAL NULL METHOD AI翻译
  作者：Hartman, Nicholas; Messana, Joseph M.; Kang, Jian; Naik, Abhijit S.; Shearon, Tempie H.; He, Kevin
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：Risk-adjusted quality measures are used to evaluate healthcare providers with respect to national norms while controlling for factors beyond their control. Existing healthcare provider profiling approaches typically assume that the between-provider variation in these measures is entirely due to meaningful differences in quality of care. However, in practice, much of the betweenprovider variation will be due to trivial fluctuations in healthcare quality or unobservable confounding risk factors....
• A BAYESIAN MACHINE LEARNING APPROACH FOR ESTIMATING HETEROGENEOUS SURVIVOR CAUSAL EFFECTS: APPLICATIONS TO A CRITICAL CARE TRIAL AI翻译
  作者：Chen, Xinyuan; Harhay, Michael O.; Tong, Guangyu; Li, Fan
  作者单位：Mississippi State University; University of Pennsylvania; Yale University
  摘要：Assessing heterogeneity in the effects of treatments has become increasingly popular in the field of causal inference and carries important implications for clinical decision-making. While extensive literature exists for studying treatment effect heterogeneity when outcomes are fully observed, there has been limited development in tools for estimating heterogeneous causal effects when patient-centered outcomes are truncated by a terminal event, such as death. Due to mortality occurring during ...
• ON THE FAIR COMPARISON OF OPTIMIZATION ALGORITHMS IN DIFFERENT MACHINES AI翻译
  作者：Arza, Etor; Ceberio, Josu; Irurozki, Ekhine; Perez, Aritz
  作者单位：Basque Center for Applied Mathematics (BCAM); University of Basque Country; IMT - Institut Mines-Telecom; Institut Polytechnique de Paris; Telecom Paris
  摘要：An experimental comparison of two or more optimization algorithms requires the same computational resources to be assigned to each algorithm. When a maximum runtime is set as the stopping criterion, all algorithms need to be executed in the same machine if they are to use the same resources. Unfortunately, the implementation code of the algorithms is not always available, which means that running the algorithms to be compared in the same machine is not always possible. And even if they are ava...