Results 231 to 240 of about 3,583,799 (330)
Performance of tests based on the area under the ROC curve for multireader diagnostic data. [PDF]
Hwang YT, Hsu YR, Su NC.
europepmc +1 more source
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao +8 more
wiley +1 more source
Ready to ROC? A tutorial on simulation-based power analyses for null hypothesis significance, minimum-effect, and equivalence testing for ROC curve analyses. [PDF]
Riesthuis P, Otgaar H, Bücken C.
europepmc +1 more source
C.S. Hong, G.C. Kim, J.A. Jeong
openaire +2 more sources
CircZNF148 stabilizes HK1 through deubiquitinase recruitment, thereby enhancing glycolysis and lactate production. Elevated lactate promotes PD‑L1 lactylation and membrane accumulation while suppressing CD8+ T‐cell cytotoxicity, collectively facilitating immune evasion and malignant progression in TNBC.
Yuhan Jin +17 more
wiley +1 more source
Symptom-Based Dispatching in an Emergency Medical Communication Centre: Sensitivity, Specificity, and the Area under the ROC Curve. [PDF]
Larribau R +7 more
europepmc +1 more source
A mitochondria‐derived tRNA half, mt‐5’‐tiRNA‐Tyr, is upregulated in colorectal cancer tissues and plasma and promotes tumor proliferation. It binds HARS2 and promotes CPT1A‐associated HARS2 K91 succinylation, disrupts HARS2–mt‐tRNA‐His association, impairs mitochondrial translation, enhances succinate‐linked metabolic reprogramming, and shows promise ...
Xinliang Gu +10 more
wiley +1 more source
An alternative parameterization for the binormal ROC curve, with applications to sizing and simulation studies. [PDF]
Hillis SL.
europepmc +1 more source
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao +6 more
wiley +1 more source

