Results 231 to 240 of about 10,572,234 (361)

Crucial parameters for precise copy number variation detection in formalin‐fixed paraffin‐embedded solid cancer samples

open access: yesMolecular Oncology, EarlyView.
This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized.
Hanne Goris   +10 more
wiley   +1 more source

Digital twins support cross-modal and cross-centric classification of mild cognitive impairment. [PDF]

open access: yesCommun Med (Lond)
Amato LG   +10 more
europepmc   +1 more source

Phenotypic and genotypic characterization of single circulating tumor cells in the follow‐up of high‐grade serous ovarian cancer

open access: yesMolecular Oncology, EarlyView.
Single circulating tumor cells (sCTCs) from high‐grade serous ovarian cancer patients were enriched, imaged, and genomically profiled using WGA and NGS at different time points during treatment. sCTCs revealed enrichment of alterations in Chromosomes 2, 7, and 12 as well as persistent or emerging oncogenic CNAs, supporting sCTC identity.
Carolin Salmon   +9 more
wiley   +1 more source

Some issues to consider when assessing concordance of death certificates with registry reports

open access: yesAustralian and New Zealand Journal of Public Health, 2004
Kirsten McKenzie, Sue Walker, Ron Casey
doaj   +1 more source

What Is the Reliability of a New Classification for Bone Defects in Revision TKA Based on Preoperative Radiographs?

open access: green, 2019
Maartje Belt   +5 more
openalex   +2 more sources

Tumor mutational burden as a determinant of metastatic dissemination patterns

open access: yesMolecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal   +4 more
wiley   +1 more source

Deep learning detection and classification of fungal and non-fungal calcifications on paranasal sinus CT imaging. [PDF]

open access: yesPLoS One
Yang Z   +9 more
europepmc   +1 more source

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