Results 131 to 140 of about 11,200,376 (224)
Machine learning workflows beyond linear models in low-data regimes. [PDF]
Dalmau D, Sigman MS, Alegre-Requena JV.
europepmc +1 more source
Using mass cytometry, we analyzed serial blood samples from patients with relapsed epithelial ovarian cancer (EOC) treated with oleclumab–durvalumab combination immunotherapy in the NSGO‐OV‐UMB1/ENGOT‐OV30 trial. Our analysis identified potential predictive, monitoring, and response biomarkers detectable through liquid biopsy. These findings facilitate
Luka Tandaric+11 more
wiley +1 more source
Leveraging pretrained language models for seizure frequency extraction from epilepsy evaluation reports. [PDF]
Abeysinghe R+4 more
europepmc +1 more source
Epithelial–mesenchymal transition (EMT) and tumor‐infiltrating lymphocytes (TILs) are associated with early breast cancer response to neoadjuvant chemotherapy (NAC). This study evaluated EMT and TIL shifts, with immunofluorescence and RNA sequencing, at diagnosis and in residual tumors as potential biomarkers associated with treatment response.
Françoise Derouane+16 more
wiley +1 more source
Uncertainty Quantification in Epigenetic Clocks via Conformalized Quantile Regression. [PDF]
Li Y+4 more
europepmc +1 more source
Molecular and functional profiling unravels targetable vulnerabilities in colorectal cancer
We used whole exome and RNA‐sequencing to profile divergent genomic and transcriptomic landscapes of microsatellite stable (MSS) and microsatellite instable (MSI) colorectal cancer. Alterations were classified using a computational score for integrative cancer variant annotation and prioritization.
Efstathios‐Iason Vlachavas+15 more
wiley +1 more source
Ultrasound-based radiomics for predicting the five major histological subtypes of epithelial ovarian cancer. [PDF]
Yang Y+5 more
europepmc +1 more source
Discussion: “A Mathematical Model Depicting the Stress-Strain Diagram and the Hysteresis Loop” (Whiteman, I. R., 1959, ASME J. Appl. Mech., 26, pp. 95–100) [PDF]
JoDean Morrow
openalex +1 more source
Cancer stem cells are associated with aggressive disease, but a deep characterization of such markers is lacking in endometrial cancer. This study uses imaging mass cytometry to explore putative cancer stem cell markers in endometrial tumors and corresponding organoid models.
Hilde E. Lien+7 more
wiley +1 more source