Goodness-of-fit indices for competing models of EFL-SSSES.
Goodness-of-fit indices for competing models of EFL-SSSES.
Yawen Wang (1578763) +1 more
core +1 more source
Nonparametric goodness-of-fit testing for parametric covariate models in pharmacometric analyses. [PDF]
Hartung N +3 more
europepmc +1 more source
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
Goodness-of-fit indices for competing models of EFL-SSES.
Goodness-of-fit indices for competing models of EFL-SSES.
Yawen Wang (1578763) +1 more
core +1 more source
Computing the Two-Sided Kolmogorov-Smirnov Distribution
We propose an algorithm to compute the cumulative distribution function of the two-sided Kolmogorov-Smirnov test statistic Dn and its complementary distribution in a fast and reliable way.
Richard Simard, Pierre L'Ecuyer
doaj
Modulation of the goodness of fit in hydrological modelling based on inner balance errors. [PDF]
Pellicer-Martínez F +4 more
europepmc +1 more source
ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller +14 more
wiley +1 more source
Goodness-of-fit two-phase sampling designs for time-to-event outcomes: a simulation study based on New York University Women's Health Study for breast cancer. [PDF]
Lee M +3 more
europepmc +1 more source
Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis
ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang +4 more
wiley +1 more source
Goodness-of-fit inference for the additive hazards regression model with clustered current status data. [PDF]
Feng Y, Wang J, Li Y.
europepmc +1 more source

