Detecting circulating tumor cells (CTCs) in blood before surgery may help predict outcomes in patients with head and neck squamous cell carcinoma (HNSCC). Here, we show when combined with tumor size and lymph node involvement from routine imaging, CTC status identifies high‐risk patients with poorer survival—offering a simple, minimally invasive tool ...
Susanne Flach +9 more
wiley +1 more source
Joint Item Response Models for Manual and Automatic Scores on Open-Ended Test Items. [PDF]
Bengs D, Brefeld U, Kroehne U, Zehner F.
europepmc +1 more source
Ignoring a Multilevel Structure in Mixture Item Response Models: Impact on Parameter Recovery and Model Selection. [PDF]
Lee WY, Cho SJ, Sterba SK.
europepmc +1 more source
PANoptosis in the pathogenesis of myelodysplastic syndromes
PANoptosis, a combination of three types of programmed cell death, is mediated by a large protein complex called a PANoptosome. In healthy bone marrow hematopoietic cells, PANoptosis is restricted by inhibitory signaling. In MDS, bone marrow cells become sensitive to the PANoptotic stimuli due to the aberrant inactivation of inhibitory signaling or ...
Rohit Thalla +4 more
wiley +1 more source
Bayesian Estimation of Generalized Log-Linear Poisson Item Response Models for Fluency Scores Using brms and Stan. [PDF]
Myszkowski N, Storme M.
europepmc +1 more source
Refining the assessment of disrupted maternal communication: Using item response models to identify central indicators of disrupted behavior. [PDF]
Haltigan JD +6 more
europepmc +1 more source
Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche +10 more
wiley +1 more source
A Transposed Bock–Aitkin EM Algorithm for Item Response Models with Many Items and Few Subjects
PRESTON DAVID BOTTER +1 more
openalex +1 more source
Explaining Person-by-Item Responses using Person- and Item-Level Predictors via Random Forests and Interpretable Machine Learning in Explanatory Item Response Models. [PDF]
Cho SJ, Amanda G, Salas J, Mueller S.
europepmc +1 more source
Obtaining Fixed Effects for Between-Within Designs in Explanatory Longitudinal Item Response Models Using Mplus. [PDF]
Cho SJ, Suh Y.
europepmc +1 more source

