Details

Vpliv izražanja receptorja za inzulinu podoben rastni dejavnik 1 (IGF1R) na preživetje pri razsejanem nedrobnoceličnem raku pljuč : doktorsko delo
ID Humar, Mojca (Author), ID Čufer, Tanja (Mentor) More about this mentor... This link opens in a new window

.pdfPDF - Presentation file, Download (1,15 MB)
MD5: FC691BCFDFB33501F247F274E20ADF12
PID: 20.500.12556/rul/9136d6e5-a24e-4350-b1cb-75b7537460ae

Language:Slovenian
Keywords:onkologija, nedrobnocelični karcinom pljuč, receptor za IGF tipa 1, sladkorna bolezen tip 2, stopnja preživetja, imunohistokemija, bioločki tumorski označevalci
Work type:Dissertation
Typology:2.08 - Doctoral Dissertation
Organization:MF - Faculty of Medicine
Place of publishing:Ljubljana
Publisher:[M. Humar]
Year:2017
Number of pages:49 f.
PID:20.500.12556/RUL-99262 This link opens in a new window
UDC:616.24-006-036(043.3)
COBISS.SI-ID:293271808 This link opens in a new window
Publication date in RUL:10.01.2018
Views:4954
Downloads:650
Metadata:XML DC-XML DC-RDF
:
HUMAR, Mojca, 2017, Vpliv izražanja receptorja za inzulinu podoben rastni dejavnik 1 (IGF1R) na preživetje pri razsejanem nedrobnoceličnem raku pljuč : doktorsko delo [online]. Doctoral dissertation. Ljubljana : M. Humar. [Accessed 22 July 2025]. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=99262
Copy citation
Share:Bookmark and Share

Secondary language

Language:English
Keywords:oncology, carcinoma non-small-cell lung, receptor IGF type 1, diabetes mellitus type 2, survival rate, immunohistochemistry, biomarkers tumor

Similar documents

Similar works from RUL:
  1. DEEP LEARNING METHODS FOR BIOMETRIC RECOGNITION BASED ON EYE INFORMATION
  2. Part of speech tagging of slovene language using deep neural networks
  3. Automatic classification of buildings with deep learning
  4. Object detection and classification in aquatic environment using convolutional neural networks
  5. Superposition and compression of deep neutral networks
Similar works from other Slovenian collections:
  1. Time series classification based on convolutional neural networks
  2. The preparation of photos' dataset and its classification using deep neural networks
  3. Prediction of geospatial raster data using convolutional neural networks
  4. Development of an advanced system for lane detection on GPU platforms
  5. Comparison of different deep neural network learning algorithms in autonomous driving

Back