2期

最新文章

• FEDERATED LEARNING OF ROBUST INDIVIDUALIZED DECISION RULES WITH APPLICATION TO HETEROGENEOUS MULTIHOSPITAL SEPSIS POPULATION AI翻译
  作者：Chen, Xinlei; Talisa, Victor B.; Tan, Xiaoqing; Qi, Zhengling; Kennedy, Jason N.; Chang, Chung-Chou H.; Seymour, Christopher W.; Tang, Lu
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; George Washington University; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
  摘要：Sepsis is a life-threatening condition affecting millions of individuals in the U.S. each year. The complexity of sepsis clinical management makes individualized treatment approaches desirable. The University of Pittsburgh Medical Center (UPMC) has collected electronic health records data of sepsis patients from multiple hospitals. The goal of this study is to derive individualized decision rules (IDRs) that could be safely applied to and uniformly improve decision-making across hospitals in t...
• A PÓLYA TREE MODELLING FRAMEWORK FOR BATCH-MARK DATA AI翻译
  作者：Rotous, Ioannis; Diana, Alex; Atechou, Leni
  作者单位：University of London; University College London; University of Essex; University of Kent
  摘要：Wildlife population surveys typically consist of multiple sampling occasions, where individuals are followed over time, enabling estimation of population size and, in open populations, of entry and exit patterns. Batch-mark (BM) surveys, where newly sampled individuals are given the same marking, often unique for each sampling occasion or each sampling period but not for each individual, provide the only viable monitoring tool for many species of amphibians, birds and fish. Modelling BM data f...
• RICE-DISTRIBUTED AUTOREGRESSIVE TIME SERIES MODELING OF MAGNITUDE FUNCTIONAL MRI DATA AI翻译
  作者：Adrian, Daniel W.; Maitra, Ranjan; Rowe, Daniel B.
  作者单位：Grand Valley State University; Iowa State University; Marquette University
  摘要：Functional magnetic resonance imaging (fMRI) data generally consist of time series image volumes of the magnitude of complex-valued observations at each voxel. However, incorporating Gaussian-based time series models and the Rice distribution-a more accurate model for the data-in the time series have been separated by a distributional mismatch. We bridge this gap by including pth-order autoregressive (AR) errors into the Gaussian model for the latent real and imaginary components underlying th...
• IS THE PRICE CAP FOR GAS USEFUL? EVIDENCE FROM EUROPEAN COUNTRIES AI翻译
  作者：Ravazzolo, Francesco; Rossini, Luca
  作者单位：BI Norwegian Business School; Free University of Bozen-Bolzano; University of Milan; Fondazione Mattei
  摘要：Since Russia's invasion of Ukraine, many countries have pledged to end or restrict their oil and gas imports to curtail Moscow's revenues and hinder its war effort. Thus, the European ministers agreed to trigger a cap on the gas price. To detect the importance of the price cap for gas, we provide a mixture representation for the gas price to detect the presence of outliers made by a truncated normal distribution and a uniform one. We focus our analysis on a unique dataset of different commodit...
• A DEEP NEURAL NETWORK TWO-PART MODEL AND FEATURE IMPORTANCE TEST FOR SEMICONTINUOUS DATA AI翻译
  作者：Zou, Baiming; Mi, Xinlei; Wan, Shiyu; Wu, Di; Xenakis, James G.; Hu, Jianhua; Zou, Fei
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Gilead Sciences; Harvard University; Columbia University
  摘要：Semicontinuous data frequently arise in clinical practice. For example, while many surgical patients still suffer from varying degrees of acute postoperative pain (POP) sometime after surgery (i.e., POP score > 0), others experience none (i.e., POP score = 0), indicating the existence of two distinct data processes at play. Existing parametric or semiparametric two-part modeling methods for this type of semicontinuous data can fail to appropriately model the two underlying data processes, as s...
• A MULTIRUN STEP-STRESS MODEL FOR TREND RENEWAL DATA WITH APPLICATIONS TO LIFETIME ASSESSMENT FOR RECHARGEABLE BATTERIES AI翻译
  作者：Tseng, Sheng-Tsaing; Hsu, Nan-Jung; Wu, Chien-Chi
  作者单位：National Tsing Hua University
  摘要：Conducting a cost-efficient lifetime-testing plan to timely assess lifetime information of a highly reliable product is often a challenging task in the manufacturing industry. Motivated by a case study of rechargeable lithium-ion batteries, this paper introduces a multirun k-level step-stress experiment, running under different stresses in repeated cycles, to collect and analyze the degradation data of reusable highly-reliable products. Specifically, we formulate the battery capacity over rech...
• COOPERATIVE DIFFERENTIAL NETWORK LEARNING WITH HUB DETECTION FOR MULTICENTER NEUROIMAGING DATA AI翻译
  作者：Chen, Hao; Guo, Dingzi; Guo, Ying; He, Yong; Liu, Dong; Liu, Lei; Yin, Yue; Zhou, Xiao-Hua
  作者单位：Shandong University; Shandong University; Emory University; Rollins School Public Health; Nanyang Technological University; Washington University (WUSTL); Shandong University; Peking University; Peking University; Peking University
  摘要：In this study we focus on Cooperative Differential Network Learning with hub detection (CDNL) for functional Magnetic Resonance Imaging (fMRI) scan from multiple research centers. As research centers may use varying scanners, imaging parameters, and other conditions that introduce heterogeneity, CDNL allows us to analyze fMRI data from various perspectives while identifying shared structures, potentially revealing the underlying mechanisms of neurological diseases. In addition, brain functiona...
• FUNCTIONAL DATA ANALYSIS WITH MÖBIUS WAVES: APPLICATIONS TO BIOMEDICAL OSCILLATORY SIGNALS AI翻译
  作者：Fernandez, Itziar; Yolanda, Larriba; Canedo, Christian; Rueda, Cris tina
  作者单位：Universidad de Valladolid
  摘要：The Frequency Modulated M & ouml;bius (FMM) approach is a contemporary and versatile tool for analyzing oscillatory signals. Within the functional data analysis framework, the FMM model offers an accurate alternative for comprehending multidimensional synchronized oscillatory signals, which are common in various fields including biology and medicine. This approach decomposes the signals into scaled M & ouml;bius waves formulated in terms of four parameters, interpreted as measures of location ...
• EFFECTS OF ADOLESCENT VICTIMIZATION ON OFFENDING: FLEXIBLE METHODS FOR MISSING DATA AND UNMEASURED CONFOUNDING AI翻译
  作者：Rubio, Mateo Dulce; Kennedy, Edward H.; Bacak, Valerio; Nagin, Daniel S.
  作者单位：Carnegie Mellon University; Carnegie Mellon University; Rutgers University System; Rutgers University New Brunswick
  摘要：The causal link between victimization and violence later in life is largely accepted but has been understudied for victimized adolescents. In this work we use the Add Health dataset, the largest nationally representative longitudinal survey of adolescents, to estimate the relationship between victimization and future offending in this population. To accomplish this, we derive a new doubly robust estimator for the average treatment effect on the treated (ATT) when the exposure and outcome are n...
• BIOMARKER DETECTION FOR DISEASE CLASSIFICATION IN LONGITUDINAL MICROBIOME DATA AI翻译
  作者：Cheng, Chao; Ma, Hanteng; Zhong, Yujie; Uhlemann, Anne-Catrin; Feng, Xingdong; Hu, Jianhua
  作者单位：Jiangxi University of Finance & Economics; Columbia University; Columbia University
  摘要：The microbiome has been found to have a close relationship with human health. Advancements in sequencing technologies have enabled in-depth studies of microbial communities and their associations with various diseases. When analyzing microbiome data, it is common to perform compositional scale normalization to ensure statistical validity. This requires special treatment to address the unique characteristics of microbiome data. Furthermore, biomedical studies often involve repeated measurements...