Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 7 min ago
PreprintAll rights reservedmedRxiv

Sensitive Glioma Detection and Recurrence Monitoring Using a Machine Learning Model Based on Circulating Monocytes

8 more authors
  1. 1Nanjing Medical University

Related

  1. Whole-genome sequencing-based tumor-informed circulating tumor DNA monitoring for early detection of recurrence in patients with solid tumors
    Mridula George, Gary S Schwartz, Wassim McHayleh +35
    The OncologistPeer-reviewedCC BY 4.0Full textOncologyPMC
  2. Platelet-programmed circulating tumor cells signal to monocytes through a candidate CD40LG-ITGA5:ITGB1 myeloid checkpoint axis in breast cancer
    S. Khoshbakht, H. Borna, M. Zarei +5
    bioRxivPreprintCC BY-NC-NDFull textOncologybioRxiv
  3. Differences in circulating levels of non-classical monocytes and associated caspase 1 activation during Staphylococcus aureus and Escherichia coli bacteremia
    Johan Courjon, Renaud Scussel, Eva Mellan +21
    VirulencePeer-reviewedCC BY 4.0Full textGeneral medicinePMC
  4. Circulating Nephrin Antibodies and Post-Transplant Recurrence of Diffuse Podocytopathies: A Systematic Review
    Noppawit Aiumtrakul, Charat Thongprayoon, Jing Miao +1
    Kidney medicinePeer-reviewedCC BY-NC-NDFull textGeneral medicineEurope PMCEurope PMCPMC
  5. From epithelial-mesenchymal transition to liquid biopsy: mechanisms of gastric cancer metastatic dissemination and circulating biomarker-guided anti-recurrence strategies
    Tianlu Chu, Peipei Yang, Peng Shu
    Frontiers in OncologyPeer-reviewedCC BY 4.0OncologyFrontiers
BibTeX
@misc{wu2026sensitive,
  title = {{Sensitive Glioma Detection and Recurrence Monitoring Using a Machine Learning Model Based on Circulating Monocytes}},
  author = {W. Wu and R. Chai and P. Xia and L. Wu and B. Yu and X. Chen and B. Pang and D. Chen and Y. Wang and N. Wang and X. Li and H. Liu and Q. Deng and F. Wan and F. Lyu and L. Wang and W. Zhang and J. Zhang and T. Jiang and Q. Wang},
  howpublished = {medRxiv},
  year = {2026},
  month = may,
  doi = {10.64898/2026.05.29.26354409},
  url = {https://www.medrxiv.org/content/10.64898/2026.05.29.26354409v2},
}
RIS
TY  - UNPB
TI  - Sensitive Glioma Detection and Recurrence Monitoring Using a Machine Learning Model Based on Circulating Monocytes
AU  - W. Wu
AU  - R. Chai
AU  - P. Xia
AU  - L. Wu
AU  - B. Yu
AU  - X. Chen
AU  - B. Pang
AU  - D. Chen
AU  - Y. Wang
AU  - N. Wang
AU  - X. Li
AU  - H. Liu
AU  - Q. Deng
AU  - F. Wan
AU  - F. Lyu
AU  - L. Wang
AU  - W. Zhang
AU  - J. Zhang
AU  - T. Jiang
AU  - Q. Wang
PY  - 2026
DA  - 2026/05/29
PB  - medRxiv
DO  - 10.64898/2026.05.29.26354409
UR  - https://www.medrxiv.org/content/10.64898/2026.05.29.26354409v2
ER  -