Results 51 to 60 of about 169,566 (212)
Predicting Immunotherapy Outcomes in NSCLC Using RNA and Pathology from Multicenter Clinical Trials
LIRA, a machine learning‐based model, is developed using transcriptomic data from 891 NSCLC patients in the OAK and POPLAR cohorts. Its predictive performance is validated in multiple external cohorts. Patients stratified by LIRA‐score exhibit distinct clinical characteristics and tumor microenvironment profiles.
Zhaojun Wang +32 more
wiley +1 more source
An alternative method of training probabilistic LR parsers [PDF]
We discuss existing approaches to train LR parsers, which have been used for statistical resolution of structural ambiguity. These approaches are nonoptimal, in the sense that a collection of probability distributions cannot be obtained. In particular, some probability distributions expressible in terms of a context-free grammar cannot be expressed in ...
M. J. NEDERHOF, SATTA, GIORGIO
openaire +2 more sources
This prospective cohort study analysing 442 mother‐offspring pairs reveals a nonlinear dose‐response relationship between late‐pregnancy serum vitamin C concentration and early offspring social competence. The strongest association was observed at low concentrations (≤ 4.9 μmol/L, β = 0.654/μmol), with diminishing effects at moderate levels (4.9–49 ...
Cui Li, Ji Jiafen, Ni Juan, Li Rui xiang
wiley +1 more source
A Minimal Span-Based Neural Constituency Parser
In this work, we present a minimal neural model for constituency parsing based on independent scoring of labels and spans. We show that this model is not only compatible with classical dynamic programming techniques, but also admits a novel greedy top ...
Andreas, Jacob +2 more
core +1 more source
Accurate projection of wind speed is essential for assessing wind energy resources and strategically planning future energy development. However, current Global Climate Models (GCMs) display discrepancies between simulated and observed near‐surface wind speed (NSWS), which limits the precise evaluation of wind energy potential.
Yanjun Lyu +5 more
wiley +1 more source
A machine learning‐guided genetic algorithm is employed to explore metal‐organic frameworks (MOFs) for CH4/N2 separation. By combining predictive modeling with adaptive evolution, the approach identifies high‐selectivity candidates featuring fsc topologies and polycyclic ligands, offering an efficient route to discovering high‐performance separation ...
Wenxuan Li +5 more
wiley +1 more source
Genomic data offer a powerful tool for studying the molecular interactions between parasites and their hosts, but they remain scarce for parasitic monogenean flatworms. This study presents the first high‐quality phased genome assembly for monogeneans (Gyrodactylus kobayashii), and uses it to predict key interacting proteins between monogenean parasite ‐
Dong Zhang +17 more
wiley +1 more source
Optimizing directly executable LR parsers [PDF]
Traditionally, LR parsers are implemented as table interpreters. A parser generator creates tables whose entries are interpreted by the parser driver. Recent research shows that much faster LR parsers can be obtained by converting the table entries into directly executed code.
openaire +1 more source
ABSTRACT Objectives Food insecurity prevalence among US university students is higher than the national average, with minoritized and first‐generation students disproportionately affected. Global and domestic US research has documented the link between food and water insecurity, though research on water insecurity—particularly on college campuses ...
Cassandra L. Workman +2 more
wiley +1 more source
Preparing, restructuring, and augmenting a French treebank: lexicalised parsers or coherent treebanks? [PDF]
We present the Modified French Treebank (MFT), a completely revamped French Treebank, derived from the Paris 7 Treebank (P7T), which is cleaner, more coherent, has several transformed structures, and introduces new linguistic analyses.
Schluter, Natalie, van Genabith, Josef
core

