Results 41 to 50 of about 139,045 (317)
Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig +9 more
wiley +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
The complex and heterogeneous nature of cancer necessitates advanced modeling techniques to better understand tumor dynamics and inform treatment strategies.
Tahmineh Azizi
doaj +1 more source
Stochastic Modeling of Congress [PDF]
We analyze the dynamics of growth of the number of congressmen supporting the resolution HR1207 to audit the Federal Reserve. The plot of the total number of co-sponsors as a function of time is of "Devil's staircase" type. The distribution of the numbers of new co-sponsors joining during a particular day (step height) follows a power law.
Simkin, M. V., Roychowdhury, V. P.
openaire +2 more sources
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky +5 more
wiley +1 more source
Modelling stochastic correlation [PDF]
This work deals with the stochastic modelling of correlation in finance. It is well known that the correlation between financial products, financial institutions, e.g., plays an essential role in pricing and evaluation of financial derivatives. Using simply a constant or deterministic correlation may lead to correlation risk, since market observations ...
Teng, Long +2 more
openaire +1 more source
Setup‐Optimized Sequencing in Job Shops: Modeling Workstation Productivity and Lateness Behavior
Setup‐optimized sequencing in job‐shop production creates a trade‐off between productivity improvement and schedule reliability. A WIP‐explicit modeling framework links sequencing‐induced productivity gains and lateness dispersion through the production operating curve.
Friederike Stefanowski +2 more
wiley +1 more source
A Literature Review of Stochastic Modeling for Phylogenetic Comparative Analysis in Trait Evolution
Evolutionary inferences from phylogenetic trees can be modeled stochastically using a range of mathematical frameworks. Among these, stochastic differential equations (SDEs) provide a particularly flexible and powerful approach to capturing the ...
Dwueng-Chwuan Jhwueng
doaj +1 more source
Multiscale Stuart-Landau Emulators: Application to Wind-Driven Ocean Gyres
The multiscale variability of the ocean circulation due to its nonlinear dynamics remains a big challenge for theoretical understanding and practical ocean modeling.
Dmitri Kondrashov +2 more
doaj +1 more source

