Skip to content
DraconiticResearch
Search Sources API
194,161 studies31 sourcesUpdated 30 min ago
Peer-reviewedCC BY-NC-ND 4.0Critical Care

Unsupervised clustering to classify patients with candidemia in intensive care: algorithmic tautology or the generation of highly anticipated new data?

Related

  1. Multi-region transcriptomics and unsupervised clustering reveal recurrent and region-specific gene signatures in Alzheimer’s disease
    Zohre Moattar-Husseini, Abbas Ahmadi, Nafiseh Mohebi
    IBRO Neuroscience ReportsPeer-reviewedCC BY-NC-NDFull textPhysiologyDOAJEurope PMCPMC
  2. Unsupervised clustering of concurrent constitutions in traditional Chinese medicine for personalized treatment
    Guangxiang Jiang, Yixing Liu, Dongran Han
    Scientific ReportsPeer-reviewedCC BY 4.0Full textGeneral medicineCrossref
  3. Unsupervised phenotypic clustering, inferential characterization, and discriminant classification of elite flatwater canoeists: neuromuscular and anthropometric determinants
    Tania Álvarez-Yates, Óscar García-García, Alba Cuba-Dorado +3
    Frontiers in physiologyPeer-reviewedCC BYFull textSurgery & anaesthesiaEurope PMCPMCEurope PMC
  4. Expert intuition vs. Algorithmic clustering: Mapping radiological subtypes in pulmonary sarcoidosis
    Justyna Sobczak, Adam J. Białas, Joanna Miłkowska-Dymanowska +5
    PLOS OnePeer-reviewedCC BY 4.0Full textMedical imaging & radiologyPLOS
  5. Sequential Time to Positivity as a Prognostic Indicator in Persistent Candidemia
    Open forum infectious diseasesPeer-reviewedCC BYFull textGeneral medicineEurope PMC
BibTeX
@article{reizine2026unsupervised,
  title = {{Unsupervised clustering to classify patients with candidemia in intensive care: algorithmic tautology or the generation of highly anticipated new data?}},
  author = {Florian Reizine and Renaud Prével and Jean-Pierre Gangneux},
  journal = {Critical Care},
  year = {2026},
  month = nov,
  doi = {10.1186/s13054-026-06396-w},
  url = {https://hal.science/hal-05850176v1},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Unsupervised clustering to classify patients with candidemia in intensive care: algorithmic tautology or the generation of highly anticipated new data?
AU  - Florian Reizine
AU  - Renaud Prével
AU  - Jean-Pierre Gangneux
PY  - 2026
DA  - 2026/11/03
JO  - Critical Care
DO  - 10.1186/s13054-026-06396-w
UR  - https://hal.science/hal-05850176v1
SN  - 1364-8535
SN  - 1466-609X
ER  -