Results 251 to 260 of about 1,229,322 (315)
Region-Based Quality Estimation Network for Large-Scale Person Re-Identification
Guanglu Song+4 more
openalex +2 more sources
Single‐cell transcriptomics of prostate cancer patient‐derived xenografts reveals distinct features of neuroendocrine (NE) subtypes. Tumours with focal NE differentiation (NED) share transcriptional programmes with adenocarcinoma, differing from large and small cell neuroendocrine prostate cancer (NEPC). Our work defines the molecular landscape of NEPC,
Rosalia Quezada Urban+12 more
wiley +1 more source
Channel semantic mutual learning for visible-thermal person re-identification. [PDF]
Zhu Y, Yang W.
europepmc +1 more source
Ensemble Learning‐Based Person Re‐identification with Multiple Feature Representations
Yun Yang+3 more
openalex +1 more source
Decrypting cancer's spatial code: from single cells to tissue niches
Spatial transcriptomics maps gene activity across tissues, offering powerful insights into how cancer cells are organised, switch states and interact with their surroundings. This review outlines emerging computational, artificial intelligence (AI) and geospatial approaches to define cell states, uncover tumour niches and integrate spatial data with ...
Cenk Celik+4 more
wiley +1 more source
Person re-identification based on multi-branch visual transformer and self-distillation. [PDF]
Chen W, Yin K, Wu Y, Hu Y.
europepmc +1 more source
Similarity-preserving Image-image Domain Adaptation for Person Re-identification
Weijian Deng+4 more
openalex +2 more sources
This study explores salivary RNA for breast cancer (BC) diagnosis, prognosis, and follow‐up. High‐throughput RNA sequencing identified distinct salivary RNA signatures, including novel transcripts, that differentiate BC from healthy controls, characterize histological and molecular subtypes, and indicate lymph node involvement.
Nicholas Rajan+9 more
wiley +1 more source
Bridging the gap: Multi‐stakeholder perspectives of molecular diagnostics in oncology
Although molecular diagnostics is transforming cancer care, implementing novel technologies remains challenging. This study identifies unmet needs and technology requirements through a two‐step stakeholder involvement. Liquid biopsies for monitoring applications and predictive biomarker testing emerge as key unmet needs. Technology requirements vary by
Jorine Arnouts+8 more
wiley +1 more source