Results 161 to 170 of about 1,366,129 (269)
SULBA: A Task-Agnostic Data Augmentation Framework for Deep Learning in Medical Image Analysis. [PDF]
Abe AA, Nyathi M.
europepmc +1 more source
Pair‐wise comparison of the CellSearch and FETCH enrichment technologies for circulating tumor cells (CTCs) from metastatic breast, prostate, and small cell lung cancer patients shows an increased capture of CTCs using FETCH enrichment. The clinical implementation of circulating tumor cells (CTCs) as a predictive tool for therapy efficacy in the ...
Michiel Stevens +6 more
wiley +1 more source
PromptSeg: An End-to-End Universal Medical Image Segmentation Method via Visual Prompts. [PDF]
Zhao M, Wang B, Shi J, An H.
europepmc +1 more source
We identify USP29 as the only DUB mirroring CA9 expression, a marker of hypoxia and HIF pathway activation associated with PCA aggressiveness. USP29 stabilizes HIF‐1α and HIF‐2α via a noncanonical mechanism that is independent of PHD/pVHL activity yet relies on proteasomal regulation, establishing USP29 as a previously unrecognized regulator of hypoxic
Amelie S Schober +16 more
wiley +1 more source
Confidence-Guided Adaptive Diffusion Network for Medical Image Classification. [PDF]
Yan Y, Xie Z, Huang W.
europepmc +1 more source
Finding novel vulnerabilities of hypomorphic BRCA1 alleles
Synthetic lethality screens performed to identify novel vulnerabilities often model complete gene loss, thereby overlooking patient‐derived hypomorphic mutations. In this study, we have performed genome‐wide CRISPR screens on BRCA1 hypomorphic mutations, showing BRCA1I26A behaves like wild‐type, while BRCA1R1699Q mimics deficiency. Furthermore, we have
Anne Schreuder +10 more
wiley +1 more source
DCANet: Disentanglement and Category-Aware Aggregation for Medical Image Segmentation. [PDF]
Li X, Huo H, Zhang C.
europepmc +1 more source

