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Employment (1)

Medizinische Universität Wien: Wien, AT

2015-10 to present
Employment
Source: Self-asserted source
Marko Grahovac

Education and qualifications (2)

Medizinische Universität Wien: Wien, AT

2019-03 to 2024-11 | PhD (Department of Biomedical Imaging and Image-guided Therapy)
Education
Source: Self-asserted source
Marko Grahovac

Fachhochschule Wiener Neustadt: Wiener Neustadt, AT

2013-09 to 2015-06 | Master of Sciensce (MedTech)
Education
Source: Self-asserted source
Marko Grahovac

Works (16)

DEBI-NN: Distance-encoding biomorphic-informational neural networks for minimizing the number of trainable parameters

Neural Networks
2023-10 | Journal article
DOI: 10.1016/j.neunet.2023.08.026
Contributors: Laszlo Papp; David Haberl; Boglarka Ecsedi; Clemens P. Spielvogel; Denis Krajnc; Marko Grahovac; Sasan Moradi; Wolfgang Drexler
Source: check_circle
Crossref

Machine learning predictive performance evaluation of conventional and fuzzy radiomics in clinical cancer imaging cohorts

European Journal of Nuclear Medicine and Molecular Imaging
2023-05 | Journal article
DOI: 10.1007/s00259-023-06127-1
Part of ISSN: 1619-7070
Part of ISSN: 1619-7089
Contributors: M. Grahovac; C. P. Spielvogel; D. Krajnc; B. Ecsedi; T. Traub-Weidinger; S. Rasul; K. Kluge; M. Zhao; X. Li; M. Hacker et al.
Source: Self-asserted source
Marko Grahovac
grade
Preferred source (of 3)‎

Automated data preparation for in vivo tumor characterization with machine learning

Frontiers in Oncology
2022-10-11 | Journal article
DOI: 10.3389/fonc.2022.1017911
Part of ISSN: 2234-943X
Contributors: Denis Krajnc; Clemens P. Spielvogel; Marko Grahovac; Boglarka Ecsedi; Sazan Rasul; Nina Poetsch; Tatjana Traub-Weidinger; Alexander R. Haug; Zsombor Ritter; Hussain Alizadeh et al.
Source: Self-asserted source
Marko Grahovac via Crossref Metadata Search

Radiogenomic markers enable risk stratification and inference of mutational pathway states in head and neck cancer

European Journal of Nuclear Medicine and Molecular Imaging
2022-09-26 | Journal article
DOI: 10.1007/s00259-022-05973-9
Part of ISSN: 1619-7089
Contributors: Clemens P. Spielvogel; Stefan Stoiber; Laszlo Papp; Denis Krajnc; Marko Grahovac; Elisabeth Gurnhofer; Karolina Trachtova; Vojtech Bystry; Asha Leisser; Bernhard Jank et al.
Source: Self-asserted source
Marko Grahovac via Crossref Metadata Search

Multi-lesion radiomics of PET/CT for non-invasive survival stratification and histologic tumor risk profiling in patients with lung adenocarcinoma

European Radiology
2022-07-28 | Journal article
DOI: 10.1007/s00330-022-08999-7
Part of ISSN: 1432-1084
Contributors: Meixin Zhao; Kilian Kluge; Laszlo Papp; Marko Grahovac; Shaomin Yang; Chunting Jiang; Denis Krajnc; Clemens P. Spielvogel; Boglarka Ecsedi; Alexander Haug et al.
Source: Self-asserted source
Marko Grahovac

A Sneak-Peek into the Physician’s Brain: A Retrospective Machine Learning-Driven Investigation of Decision-Making in TAVR versus SAVR for Young High-Risk Patients with Severe Symptomatic Aortic Stenosis

Journal of Personalized Medicine
2021-10-22 | Journal article
DOI: 10.3390/jpm11111062
Part of ISSN: 2075-4426
Contributors: Ena Hasimbegovic; László Papp; Marko Grahovac; Denis Krajnc; Thomas Poschner; Waseem Hasan; Martin Andreas; Christoph Gross; Andreas Strouhal; Georg Delle-Karth et al.
Source: Self-asserted source
Marko Grahovac

3D ultrasound guided navigation system with hybrid image fusion

Scientific Reports
2021-04-23 | Journal article
DOI: 10.1038/s41598-021-86848-1
Part of ISSN: 2045-2322
Contributors: David Iommi; Alejandra Valladares; Michael Figl; Marko Grahovac; Gabor Fichtinger; Johann Hummel
Source: Self-asserted source
Marko Grahovac

Breast Tumor Characterization Using [18F]FDG-PET/CT Imaging Combined with Data Preprocessing and Radiomics

Cancers
2021-03-12 | Journal article
DOI: 10.3390/cancers13061249
Contributors: Denis Krajnc; Laszlo Papp; Thomas S. Nakuz; Heinrich F. Magometschnigg; Marko Grahovac; Clemens P. Spielvogel; Boglarka Ecsedi; Zsuzsanna Bago-Horvath; Alexander Haug; Georgios Karanikas et al.
Source: check_circle
Crossref
grade
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in vivo D’Amico score for low-high risk and biochemical recurrence prediction in prostate patients with PET/MRI and machine learning

Nuklearmedizin
2020-04 | Conference paper
DOI: 10.1055/s-0040-1708140
Part of ISSN: 2567-6407
Contributors: L Papp; CP Spielvogel; D Krajnc; M Grahovac; T Beyer; M Hartenbach; M Hacker
Source: Self-asserted source
Marko Grahovac via Crossref Metadata Search

Understanding gender pattern differences in MET-PET Glioma patients with radiomics analysis

Nuklearmedizin
2020-04 | Conference paper
DOI: 10.1055/s-0040-1708295
Part of ISSN: 2567-6407
Contributors: L Papp; S Rasul; M Weber; M Grahovac; T Beyer; M Hacker; T Traub-Weidinger
Source: Self-asserted source
Marko Grahovac via Crossref Metadata Search

Comparison of machine learning-driven lesion classifiers in prostate PET/MRI cases over different repeatability categories of radiomic features

2019-03 | Conference abstract
DOI: 10.1055/s-0039-1683672
Source: Self-asserted source
Marko Grahovac

Explorative analysis of retrospective data of patients with esophageal cancer at the Department of Nuclear Medicine at the Medical University of Vienna: Predicting 30-month survival and progress-free survival using Supervised Machine Learning

Nuklearmedizin
2019-03 | Conference paper
DOI: 10.1055/s-0039-1683669
Part of ISSN: 2567-6407
Contributors: T Nakuz; K Monschein; L Papp; M Grahovac; W Wadsak; M Mitterhauser; AR Haug; M Hacker; G Karanikas
Source: Self-asserted source
Marko Grahovac via Crossref Metadata Search

Glioma Survival Prediction with Combined Analysis of In Vivo 11C-MET PET Features, Ex Vivo Features, and Patient Features by Supervised Machine Learning

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
2018 | Journal article
DOI: 10.2967/jnumed.117.202267
Source: Self-asserted source
Marko Grahovac

Optimized feature extraction for radiomics analysis of 18F-FDG-PET imaging

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
2018 | Journal article
DOI: 10.2967/jnumed.118.217612
Source: Self-asserted source
Marko Grahovac
grade
Preferred source (of 2)‎

PSMA Ligand PET/MRI for Primary Prostate Cancer: Staging Performance and Clinical Impact

Clinical cancer research : an official journal of the American Association for Cancer Research
2018 | Journal article
DOI: 10.1158/1078-0432.ccr-18-0768
Source: Self-asserted source
Marko Grahovac

PET/CT radiomics and machine learning enable non-invasive survival stratification and histologic tumor risk profiling in patients with lung adenocarcinoma

Other
DOI: 10.21203/rs.3.rs-771161/v1
Contributors: Meixin Zhao; Kilian Kluge; Laszlo Papp; Marko Grahovac; Shaomin Yang; Chunting Jiang; Denis Krajnc; Clemens P. Spielvogel; Boglarka Ecsedi; Alexander Haug et al.
Source: Self-asserted source
Marko Grahovac via Crossref Metadata Search
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