Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 33 for “"Joint Modeling"”.
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Joint Modeling of Tumor Size and Time-to-Event
… model these two components simultaneously, the joint modeling approach which can reduce potential biases and improve the efficiency in estimating treatment effects becomes increasingly important. In this work, we proposed a joint model where a nonlinear mixed-effect model with both exponential …
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JOINT MODELING OF MULTIVARIATE LONGITUDINAL DATA AND COMPETING RISKS DATA
… due to informative dropout, one has to jointly model the longitudinal data and the timeto event outcomes in order to obtain valid inferences. Recently, there has been much attention paid to the joint analysis of single longitudinal measurements and single time to event data. A natural …
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Joint modeling receiver functions and autocorrelograms to estimate crustal structure in the presence of deep sediments.
… functions and autocorrelograms. Waveform modeling takes significant computational power, so non-linear global optimization methods are used to efficiently navigate the parameter space. Our first study applies this method to the Permian Basin. We matched the expected basin structure with …
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Seismic site characterization through joint modeling of complementary data functionals, with applications to Santo Domingo, Dominican Republic.
… seismic "site characterization" through joint modeling of horizontal to vertical spectral ratios (HVSR) and surface wave dispersion, performed via refraction microtremor (ReMi). Fitting of data functionals by synthetics is driven by global optimization. The products of this approach are …
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Seismic site characterization via joint modeling of horizontal-to-vertical spectral ratios and surface wave dispersion : developing and validating a geophysical tool for deciphering Quaternary stratigraphic architecture of the Monahans dune field, West Texas.
… are subject to ambiguity and nonuniqueness. We jointly model HVSR and surface wave phase velocity dispersion measurements via global optimization to produce best-fit 1D shear wave velocity models for the interpretation of geologic structure and use statistical tools, including posterior …
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Dynamic Prediction of Disease Progression With Longitudinal Data
… of longitudinal and time-to-event data through joint modeling, a prevalent technique. Alongside joint modeling, landmark modeling stands as another key approach in the realm of longitudinal studies. These methodologies are instrumental in dynamically predicting clinical events by utilizing …
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Longitudinal latent class and joint modelling of antiretroviral adherence
… HIV in South Africa using advanced statistical modeling techniques. Utilizing data from the ADD-ART study, a prospective cohort of 238 adults on ART in Cape Town, the research employs survival analysis, joint modeling, and longitudinal latent class analysis to compare di↵erent adherence …
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Statistical methods for ChIP-seq and microbiome studies using next-generation DNA sequencing data
… replicates. Very few methodologies exist for the joint analysis of replicated ChIP-seq data, with approaches ranging from combining the results of analyzing replicates individually to joint modeling of all replicates. Combining the results of individual replicates analyzed separately can lead to …
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Semiparametric Bayesian Joint Model With Variable Selection
… time-to-event histories. Recently, methods for jointly modeling longitudinal and survival data have gained popularity in the statistical literature. In this dissertation, we consider the problem of variable selection in a joint modeling framework where longitudinal and survival data are modeled …
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Probabilistic generative modeling of speech
… be more accurately estimated if they are modeled jointly; speech synthesis also benefits from joint modeling. This thesis proposes a probabilistic generative model for speech called the Probabilistic Acoustic Tube (PAT). The highlights of the model are threefold. First, it is among the very first …
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Joint models for longitudinal and survival data
… until the occurrence of the event or censoring. Joint models for longitudinal and time-to-event data can be used to estimate the association between the characteristics of the longitudinal measures over time and survival time. We developed a maximum-likelihood method to joint model multiple …
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VoxelPrompt: A Vision-Language Agent for Grounded Medical Image Analysis
… that tackles diverse radiological tasks through joint modeling of natural language, image volumes, and analytical metrics. VoxelPrompt is multi-modal and versatile, leveraging the flexibility of language interaction while providing quantitatively-grounded image analysis. Given a variable number …
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Response Adaptive Design using Auxiliary and Primary Outcomes
… outcomes. We demonstrate several methods of joint modeling the auxiliary and primary outcomes. Through simulation studies, we show that the bivariate adaptive design is more effective in assigning patients to better treatments as compared with univariate optimal and balanced designs. As …
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Formality Style Transfer Within and Across Languages with Limited Supervision
… then turn to neural sequence to sequence models. Joint modeling of formality transfer and machine translation enables formality control in machine translation without dedicated training examples. Along the way, we also improve low-resource neural machine translation.
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Separate and Joint Analysis of Longitudinal and Survival Data
… of Bayesian Hierarchical Models and Win-BUGS to jointly model the survival data and the longitudinal data—mass. The results of the joint analysis indicate that the use of ultrasound and water-soluble microcapsules have no negative effect on survival. In fact, there appears to be a positive effect …
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Multimodal Learning for Disease Diagnosis and Progression Modeling
<p>Accurate diagnosis and progression modeling of Alzheimer’s Disease (AD) are critical for effective intervention, disease monitoring, and patient care. Traditional approaches rely on a single modality, such as clinical assessments, neuroimaging, or genetic markers, but may fail in capturing the …
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Nonlinear Cyclic Truss Model for Beam-Column Joints of Non-ductile RC Frames
… areas with seismic hazards. The beam-to-column joints of these frames are key components that have a significant impact on the structure's behavior. Modern detailing provides sufficient strength within these joints to transfer the forces between the beams and the columns during a seismic event, …
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Understanding stories via event sequence modeling
… specificity; Third, we improve event sequence modeling by joint modeling of semantic information and incorporating background knowledge. Each of the above three research problems poses both conceptual and computational challenges. For event extraction, we find that Semantic Role Labeling (SRL) …
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Numerical Modeling Methodology for Weak Rock Masses in Nevada gold mines
… to take into consideration the effect of jointing using discrete fracture network (DFN) and rock bolts in 3DEC. Sensitivity studies were performed on over 200 time dependent numerical models to understand the effect of various rock support design parameters on different excavation sizes …
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Bayesian models for visual information retrieval
… of the most challenging problems faced by these: joint modeling of color and texture, objective guidelines for controlling the trade-off between feature transformation and feature representation, and unified support for local and global queries without requiring image segmentation. The new …
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