Results 51 to 60 of about 41,785 (303)
ABSTRACT Objective To investigate which baseline clinical and imaging characteristics best predict TSPO‐PET‐measurable reduction in glial activation following treatment of multiple sclerosis (MS), to utilize this information for designing more efficient biomarker‐based clinical trials targeting glial activation.
Marlene T. Morch +5 more
wiley +1 more source
Objective We aimed to construct and evaluate the first laboratory‐based frailty index (FI‐Lab) for predicting adverse outcomes in systemic lupus erythematosus (SLE) and to compare its predictive ability to that of an existing clinical FI. Methods We used data from a single‐center prospective cohort of adult patients with SLE whose baseline visit ...
Grace Burns +2 more
wiley +1 more source
Change of support for zero-inflated data: deriving fine-scale species distribution inferences from spatially aggregated data [PDF]
In environmental sciences, data are often available at a coarse resolution. This can result in a mismatch between the data resolution and the resolution at which process inference should be made.
Alglave, Baptiste +6 more
core +1 more source
High Health Care Utilization Preceding Diagnosis With Juvenile Idiopathic Arthritis
Objective Although early diagnosis improves long‐term outcomes, patients with juvenile idiopathic arthritis (JIA) often experience prolonged, circuitous paths to diagnosis. To inform diagnostic improvement, we sought to characterize health care utilization in the year preceding diagnosis. Methods We identified 10,021 patients with an incident diagnosis
Anna Costello +5 more
wiley +1 more source
This article proposes a convergent adaptive observer for a damped wave PDE and an infinite‐dimensional ODE coupled in cascade using sampled‐in‐space ODE state measurements. The proposed observer estimates the distributed states of the PDE and ODE along with unknown PDE parameters and spatial input.
Zehor Belkhatir +2 more
wiley +1 more source
Zero‐inflated prediction model in software‐fault data
Software fault data with many zeroes in addition to large non‐zero values are common in the software estimation area. A two‐component prediction approach that provides a robust way to predict this type of data is introduced in this study. This approach allows to combine parametric and non‐parametric models to improve the prediction accuracy.
Roberta A. de A. Fagundes +2 more
openaire +1 more source
Zero-Inflated Data Analysis Using Graph Neural Networks with Convolution
Zero-inflated count data are characterized by an excessive frequency of zeros that cannot be adequately analyzed by a single distribution, such as Poisson or negative binomial.
Sunghae Jun
doaj +1 more source
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
Maximum-Likelihood Estimation for the Zero-Inflated Polynomial-Adjusted Poisson Distribution
We propose the zero-inflated Polynomially Adjusted Poisson (zPAP) model. It extends the usual zero-inflated Poisson by multiplying the Poisson kernel with a nonnegative polynomial, enabling the model to handle extra zeros, overdispersion, skewness, and ...
Jong-Seung Lee, Hyung-Tae Ha
doaj +1 more source
This study shows that superalloys used in aircraft engine disks become much more prone to deformation at high temperatures if they have been strained during manufacturing. This effect increases with the level of prior strain but eventually reaches a limit.
Fabio Machado Alves da Fonseca +9 more
wiley +1 more source

