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最新文章

• A BAYESIAN GROUP SELECTION WITH COMPOSITIONAL RESPONSES FOR ANALYSIS OF RADIOLOGIC TUMOR PROPORTIONS AND THEIR GENOMIC DETERMINANTS AI翻译
  作者：Chekouo, Thierry; Stingo, Francesco C.; Mohammed, Shariq; Rao, Arvind; Baladandayuthapani, Eerabhadran
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Florence; Boston University; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：Volumetric imaging features are used in cancer research to determine the size and the composition of a tumor and have been shown to be prog-nostic of overall survival. In this paper we focus on the analysis of tumor component proportions of brain cancer patients collected through The Can-cer Genome Atlas (TCGA) project. Our main goal is to identify pathways and corresponding genes that can explain the heterogeneity of the composition of a brain tumor. In particular, we focus on the glioblastom...
• MULTIMODEL ENSEMBLE ANALYSIS WITH NEURAL NETWORK GAUSSIAN PROCESSES AI翻译
  作者：Harris, Trevor; Li, Bo; Sriver, Ryan
  作者单位：Texas A&M University System; Texas A&M University College Station; University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：Multimodel ensemble analysis integrates information from multiple climate models into a unified projection. However, existing integration approaches, based on model averaging, can dilute fine-scale spatial information and incur bias from rescaling low-resolution climate models. We propose a statistical approach, called NN-GPR, using Gaussian process regression (GPR) with an infinitely wide deep neural network based covariance function. NN-GPR requires no assumptions about the relationships bet...
• BAYESIAN LEARNING OF COVID-19 VACCINE SAFETY WHILE INCORPORATING ADVERSE EVENTS ONTOLOGY AI翻译
  作者：Zhao, Bangyao; Zhong, Yuan; Kang, Jian; Zhao, Lili
  作者单位：University of Michigan System; University of Michigan
  摘要：While vaccines are crucial to end the COVID-19 pandemic, public confidence in vaccine safety has always been vulnerable. Many statistical methtem) database to study the safety of COVID-19 vaccines. However, none of these methods considered the adverse event (AE) ontology. AEs are naturally related; for example, events of retching, dysphagia, and reflux are all related to an abnormal digestive system. Explicitly bringing AE relationships into the model can aid in the detection of true AE signal...
• BAYESIAN HIERARCHICAL MODELING AND ANALYSIS FOR ACTIGRAPH DATA FROM WEARABLE DEVICES AI翻译
  作者：Di Loro, Pierfrancesco Alaimo; Mingione, Marco; Lipsitt, Jonah; Batteate, Christina M.; Jerrett, Michael; Banerjee, Sudipto
  作者单位：Universita LUMSA; Roma Tre University; University of California System; University of California Los Angeles; University of California System; University of California Los Angeles; University of California System; University of California Los Angeles
  摘要：The majority of Americans fail to achieve recommended levels of physical activity, which leads to numerous preventable health problems, such as diabetes, hypertension, and heart diseases. This has generated substantial interest in monitoring human activity to gear interventions toward environmental features that may relate to higher physical activity. Wearable devices, such as wrist-worn sensors that monitor gross motor activity (actigraph units) continuously record the activity levels of a su...
• A BAYESIAN DECISION FRAMEWORK FOR OPTIMIZING SEQUENTIAL COMBINATION ANTIRETROVIRAL THERAPY IN PEOPLE WITH HIV AI翻译
  作者：Jin, Wei; Ni, Yang; O'Halloran, Jane; Spence, Amanda B.; Rubin, Leah H.; Xu, Yanxun
  作者单位：Johns Hopkins University; Texas A&M University System; Texas A&M University College Station; Washington University (WUSTL); Georgetown University; Johns Hopkins University; Johns Hopkins University
  摘要：Numerous adverse effects (e.g., depression) have been reported for combination antiretroviral therapy (cART) despite its remarkable success in viral suppression in people with HIV (PWH). To improve long-term health outcomes for PWH, there is an urgent need to design personalized optimal cART with the lowest risk of comorbidity in the emerging field of precision medicine for HIV. Large-scale HIV studies offer researchers unprecedented opportunities to optimize personalized cART in a data-driven...
• SEQUENTIAL MONTE CARLO FOR SAMPLING BALANCED AND COMPACT REDISTRICTING PLANS AI翻译
  作者：Mccartan, Cory; Imai, Kosuke
  作者单位：Harvard University
  摘要：Random sampling of graph partitions under constraints has become a popular tool for evaluating legislative redistricting plans. Analysts detect partisan gerrymandering by comparing a proposed redistricting plan with an ensemble of sampled alternative plans. For successful application sampling methods must scale to maps with a moderate or large number of districts, incorporate realistic legal constraints, and accurately and efficiently sample from a selected target distribution. Unfortunately, ...
• DEBIASED LASSO FOR STRATIFIED COX MODELS WITH APPLICATION TO THE NATIONAL KIDNEY TRANSPLANT DATA AI翻译
  作者：Xia, Lu; Nan, Bin; Li, Yi
  作者单位：University of Michigan System; University of Michigan; University of California System; University of California Irvine
  摘要：The Scientific Registry of Transplant Recipients (SRTR) system has be -come a rich resource for understanding the complex mechanisms of graft failure after kidney transplant, a crucial step for allocating organs effectively and implementing appropriate care. As transplant centers that treated patients might strongly confound graft failures, Cox models stratified by centers can eliminate their confounding effects. Also, since recipient age is a proven non-modifiable risk factor, a common practi...
• A MULTIAGENT REINFORCEMENT LEARNING FRAMEWORK FOR OFF-POLICY EVALUATION IN TWO-SIDED MARKETS AI翻译
  作者：Shi, Chengchun; Wan, Runzhe; Song, Ge; Luo, Shikai; Zhu, Hongtu; Song, Rui
  作者单位：University of London; London School Economics & Political Science; North Carolina State University; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
  摘要：The two-sided markets, such as ride-sharing companies, often involve a group of subjects who are making sequential decisions across time and/or location. With the rapid development of smart phones and internet of things, they have substantially transformed the transportation landscape of human beings. In this paper we consider large-scale fleet management in ride-sharing companies that involve multiple units in different areas receiving sequences of products (or treatments) over time. Major te...
• COMPRESSED SPECTRAL SCREENING FOR LARGE-SCALE DIFFERENTIAL CORRELATION ANALYSIS WITH APPLICATION IN SELECTING GLIOBLASTOMA GENE MODULES AI翻译
  作者：Li, Tianxi; Tang, Xiwei; Chatrath, Ajay
  作者单位：University of Virginia; Washington University (WUSTL); Saint Louis University
  摘要：Differential coexpression analysis has been widely applied by scientists in understanding the biological mechanisms of diseases. However, the unknown differential patterns are often complicated; thus, models based on simplified parametric assumptions can be ineffective in identifying the differences. Meanwhile, the gene expression data involved in such analysis are in extremely high dimensions by nature, whose correlation matrices may not even be computable. Such a large scale seriously limits...
• A PENALIZED COMPLEXITY PRIOR FOR DEEP BAYESIAN TRANSFER LEARNING WITH APPLICATION TO MATERIALS INFORMATICS AI翻译
  作者：Abba, Mohamed A.; Williams, Jonathan P.; Reich, Brian J.
  作者单位：North Carolina State University
  摘要：A key task in the emerging field of materials informatics is to use ma-chine learning to predict a material's properties and functions. A fast and accurate predictive model allows researchers to more efficiently identify or construct a material with desirable properties. As in many fields, deep learn-ing is one of the state-of-the art approaches, but fully training a deep learn-ing model is not always feasible in materials informatics due to limitations on data availability, computational reso...