Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma

P. Rauch; H. Stefanits; M. Aichholzer; C. Serra; D. Vorhauer; H. Wagner; P. Böhm; S. Hartl; I. Manakov; M. Sonnberger; E. Buckwar; F. Ruiz-Navarro; K. Heil; M. Glöckel; J. Oberndorfer; S. Spiegl-Kreinecker; K. Aufschnaiter-Hiessböck; S. Weis; A. Leibetseder; W. Thomae; T. Hauser; C. Auer; S. Katletz; A. Gruber; M. Gmeiner

doi:10.1038/s41598-023-36298-8

Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma

P. Rauch
, H. Stefanits^*
, M. Aichholzer
, C. Serra
, D. Vorhauer
, H. Wagner
, P. Böhm
, S. Hartl
, I. Manakov
, M. Sonnberger
, E. Buckwar
, F. Ruiz-Navarro
, K. Heil
, M. Glöckel
, J. Oberndorfer
, S. Spiegl-Kreinecker
, K. Aufschnaiter-Hiessböck
, S. Weis
, A. Leibetseder
, W. Thomae

T. Hauser, C. Auer, S. Katletz, A. Gruber, M. Gmeiner

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	9494
Number of pages	12
Journal	Scientific Reports
Volume	13
Issue number	1
DOIs	https://doi.org/10.1038/s41598-023-36298-8
Publication status	Published - Dec 2023

Fields of science

302051 Neurosurgery
101018 Statistics
502051 Economic statistics
105108 Geostatistics
101029 Mathematical statistics
102009 Computer simulation
101026 Time series analysis
101024 Probability theory
502025 Econometrics
504006 Demography
305907 Medical statistics
504004 Population statistics
509013 Social statistics
509 Other Social Sciences
106007 Biostatistics
302013 Medical diagnostics
302071 Radiology
504007 Empirical social research
101007 Financial mathematics
303039 Radiological technology
302043 Magnetic resonance imaging (MRI)
302010 Computed tomography (CT)
302070 Radiodiagnostics
101019 Stochastics
101014 Numerical mathematics
101 Mathematics
301101 General pathology
301108 Molecular pathology
302052 Neurology

JKU Focus areas

Digital Transformation
Sustainable Development: Responsible Technologies and Management

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Cite this

Rauch, P., Stefanits, H., Aichholzer, M., Serra, C., Vorhauer, D., Wagner, H., Böhm, P., Hartl, S., Manakov, I., Sonnberger, M., Buckwar, E., Ruiz-Navarro, F., Heil, K., Glöckel, M., Oberndorfer, J., Spiegl-Kreinecker, S., Aufschnaiter-Hiessböck, K., Weis, S., Leibetseder, A., ... Gmeiner, M. (2023). Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma. Scientific Reports, 13(1), Article 9494. https://doi.org/10.1038/s41598-023-36298-8

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title = "Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma",

author = "P. Rauch and H. Stefanits and M. Aichholzer and C. Serra and D. Vorhauer and H. Wagner and P. B{\"o}hm and S. Hartl and I. Manakov and M. Sonnberger and E. Buckwar and F. Ruiz-Navarro and K. Heil and M. Gl{\"o}ckel and J. Oberndorfer and S. Spiegl-Kreinecker and K. Aufschnaiter-Hiessb{\"o}ck and S. Weis and A. Leibetseder and W. Thomae and T. Hauser and C. Auer and S. Katletz and A. Gruber and M. Gmeiner",

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year = "2023",

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doi = "10.1038/s41598-023-36298-8",

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Rauch, P, Stefanits, H, Aichholzer, M, Serra, C, Vorhauer, D, Wagner, H, Böhm, P, Hartl, S, Manakov, I, Sonnberger, M , Buckwar, E , Ruiz-Navarro, F , Heil, K , Glöckel, M , Oberndorfer, J , Spiegl-Kreinecker, S , Aufschnaiter-Hiessböck, K , Weis, S , Leibetseder, A, Thomae, W, Hauser, T , Auer, C, Katletz, S, Gruber, A & Gmeiner, M 2023, 'Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma', Scientific Reports, vol. 13, no. 1, 9494. https://doi.org/10.1038/s41598-023-36298-8

TY - JOUR

T1 - Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma

AU - Rauch, P.

AU - Stefanits, H.

AU - Aichholzer, M.

AU - Serra, C.

AU - Vorhauer, D.

AU - Wagner, H.

AU - Böhm, P.

AU - Hartl, S.

AU - Manakov, I.

AU - Sonnberger, M.

AU - Buckwar, E.

AU - Ruiz-Navarro, F.

AU - Heil, K.

AU - Glöckel, M.

AU - Oberndorfer, J.

AU - Spiegl-Kreinecker, S.

AU - Aufschnaiter-Hiessböck, K.

AU - Weis, S.

AU - Leibetseder, A.

AU - Thomae, W.

AU - Hauser, T.

AU - Auer, C.

AU - Katletz, S.

AU - Gruber, A.

AU - Gmeiner, M.

PY - 2023/12

Y1 - 2023/12

UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258197/pdf/41598_2023_Article_36298.pdf

UR - https://www.scopus.com/pages/publications/85161678257

U2 - 10.1038/s41598-023-36298-8

DO - 10.1038/s41598-023-36298-8

M3 - Article

C2 - 37302994

SN - 2045-2322

VL - 13

JO - Scientific Reports

JF - Scientific Reports

IS - 1

M1 - 9494

ER -

Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma

Fields of science

JKU Focus areas

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