Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade.

Röbeck P, Franzén B, Cantera-Ahlman R, Dragomir A, Auer G, Jorulf H, Jacobsson SP, Viktorsson K, Lewensohn R, Häggman M, Ladjevardi S.

Open source

DOI
10.1111/cyt.13226
Published
2023-03-20
Container
Cytopathology
Publisher
Not recorded
Open access
no

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BibTeX

@article{allodium:10.1111/cyt.13226,
  title = {Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade.},
  author = {Röbeck P and  Franzén B and  Cantera-Ahlman R and  Dragomir A and  Auer G and  Jorulf H and  Jacobsson SP and  Viktorsson K and  Lewensohn R and  Häggman M and  Ladjevardi S.},
  year = {2023},
  journal = {Cytopathology},
  doi = {10.1111/cyt.13226},
  url = {https://doi.org/10.1111/cyt.13226}
}

RIS

TY  - JOUR
TI  - Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade.
AU  - Röbeck P
AU  -  Franzén B
AU  -  Cantera-Ahlman R
AU  -  Dragomir A
AU  -  Auer G
AU  -  Jorulf H
AU  -  Jacobsson SP
AU  -  Viktorsson K
AU  -  Lewensohn R
AU  -  Häggman M
AU  -  Ladjevardi S.
PY  - 2023
JO  - Cytopathology
DO  - 10.1111/cyt.13226
UR  - https://doi.org/10.1111/cyt.13226
ER  - 

APA

P, R., B, F., R, C., A, D., G, A., H, J., SP, J., K, V., R, L., M, H., & S., L. (2023). Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade.. Cytopathology. https://doi.org/10.1111/cyt.13226

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