Skip to main content

Detail

Laszlo Papp
Laszlo Papp

Center for Medical Physics and Biomedical Engineering
Position: PHD Student

ORCID: 0000-0002-9049-9989
T +43 1 40400 61310
laszlo.papp@meduniwien.ac.at

Keywords

Artificial Intelligence

Research group(s)

Research interests

Machine learning, image processing, personalized medicine, tumour characterization

Techniques, methods & infrastructure

Techniques, Methods: In vivo feature engineering, Embedded feature selection, Stacked ensemble learning, Monte Carlo cross-validation

Infrastructure: high-performance cloud computing (ITSC)

Selected publications

  1. Papp, L. et al., 2017. Glioma survival prediction with the combined analysis of in vivo 11C-MET-PET, ex vivo and patient features by supervised machine learning. Journal of Nuclear Medicine, p.jnumed.117.202267. Available at: http://dx.doi.org/10.2967/jnumed.117.202267.
  2. Lützen, U. et al., 2016. A study on the value of computer-assisted assessment for SPECT/CT-scans in sentinel lymph node diagnostics of penile cancer as well as clinical reliability and morbidity of this procedure. Cancer Imaging, 16(1). Available at: http://dx.doi.org/10.1186/s40644-016-0087-z.
  3. Perlaki, G. et al., 2016. Validation of an automated morphological MRI-based 123I-FP-CIT SPECT evaluation method. Parkinsonism & Related Disorders, 29, pp.24-29. Available at: http://dx.doi.org/10.1016/j.parkreldis.2016.06.001.
  4. Salamon, J. et al., 2015. Nerve Sheath Tumors in Neurofibromatosis Type 1: Assessment of Whole-Body Metabolic Tumor Burden Using F-18-FDG PET/CT M. Katoh, ed. PLOS ONE, 10(12), p.e0143305. Available at: http://dx.doi.org/10.1371/journal.pone.0143305.