Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz

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Publikationen

Suchbegriffe: DEEP LEARNING, . Treffer: 95

2025

Bennetot, A; Donadello, I; El Haouari, AE; Dragoni, M; Frossard, T; Wagner, B; Sarranti, A; Tulli, S; Trocan, M; Chatila, R; Holzinger, A; Garcez, AD; Díaz-Rodríguez, N A Practical Tutorial on Explainable AI Techniques
ACM COMPUT SURV. 2025; 57(2): 50 Doi: 10.1145/3670685
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Festag, S; Herberger, S; Spreckelsen, C; Krefting, D; Fietze, I; Penzel, T; Marschik, PB; Spicher, N Age estimation for disorder characterization from pediatric polysomnograms
BIOMED SIGNAL PROCES. 2025; 106: 107701 Doi: 10.1016/j.bspc.2025.107701
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Holzinger, A; Zatloukal, K; Müller, H Is human oversight to AI systems still possible?
N Biotechnol. 2025; 85: 59-62. Doi: 10.1016/j.nbt.2024.12.003
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Khateri, P; Koottungal, T; Wong, D; Strauss, RW; Janeschitz-Kriegl, L; Pfau, M; Schmetterer, L; Scholl, HPN Looking outside the box with a pathology aware AI approach for analyzing OCT retinal images in Stargardt disease.
Sci Rep. 2025; 15(1): 4739 Doi: 10.1038/s41598-025-85213-w [OPEN ACCESS]
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Kulvicius, T; Zhang, D; Poustka, L; Bölte, S; Jahn, L; Flügge, S; Kraft, M; Zweckstetter, M; Nielsen-Saines, K; Wörgötter, F; Marschik, PB Deep learning empowered sensor fusion boosts infant movement classification.
Commun Med (Lond). 2025; 5(1):16 Doi: 10.1038/s43856-024-00701-w [OPEN ACCESS]
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Till, H; Esposito, C; Yeung, CK; Patkowski, D; Shehata, S; Rothenberg, S; Singer, G; Till, T Artificial intelligence based surgical support for experimental laparoscopic Nissen fundoplication.
Front Pediatr. 2025; 13:1584628 Doi: 10.3389/fped.2025.1584628 [OPEN ACCESS]
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Till, T; Scherkl, M; Stranger, N; Singer, G; Hankel, S; Flucher, C; Hržić, F; Štajduhar, I; Tschauner, S Impact of test set composition on AI performance in pediatric wrist fracture detection in X-rays.
Eur Radiol. 2025; Doi: 10.1007/s00330-025-11669-z
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2024

Abdulnazar, A; Kugic, A; Schulz, S; Stadlbauer, V; Kreuzthaler, M O2 supplementation disambiguation in clinical narratives to support retrospective COVID-19 studies.
BMC Med Inform Decis Mak. 2024; 24(1): 29 Doi: 10.1186/s12911-024-02425-2 [OPEN ACCESS]
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Bartl-Pokorny, KD; Zitta, C; Beirit, M; Vogrinec, G; Schuller, BW; Pokorny, FB Focused review on artificial intelligence for disease detection in infants
FRONT DIGIT HEALTH. 2024; 6: 1459640 Doi: 10.3389/fdgth.2024.1459640 [OPEN ACCESS]
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Bogaerts, JM; Steenbeek, MP; Bokhorst, JM; van, Bommel, MH; Abete, L; Addante, F; Brinkhuis, M; Chrzan, A; Cordier, F; Devouassoux-Shisheboran, M; Fernández-Pérez, J; Fischer, A; Gilks, CB; Guerriero, A; Jaconi, M; Kleijn, TG; Kooreman, L; Martin, S; Milla, J; Narducci, N; Ntala, C; Parkash, V; de, Pauw, C; Rabban, JT; Rijstenberg, L; Rottscholl, R; Staebler, A; Van, de, Vijver, K; Zannoni, GF; van, Zanten, M; de, Hullu, JA; Simons, M; van, der, Laak, JA, , AI‐STIC, Study, Group Assessing the impact of deep-learning assistance on the histopathological diagnosis of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes.
J Pathol Clin Res. 2024; 10(6):e70006 Doi: 10.1002/2056-4538.70006 [OPEN ACCESS]
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Del Ser, J; Barredo-Arrieta, A; Díaz-Rodríguez, N; Herrera, F; Saranti, A; Holzinger, A On generating trustworthy counterfactual explanations
INFORM SCIENCES. 2024; 655: 119898 Doi: 10.1016/j.ins.2023.119898
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Hadzic, A; Urschler, M; Press, JA; Riedl, R; Rugani, P; Štern, D; Kirnbauer, B Evaluating a Periapical Lesion Detection CNN on a Clinically Representative CBCT Dataset-A Validation Study.
J Clin Med. 2023; 13(1): Doi: 10.3390/jcm13010197 [OPEN ACCESS]
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Hausleitner, C; Mueller, H; Holzinger, A; Pfeifer, B Collaborative weighting in federated graph neural networks for disease classification with the human-in-the-loop.
Sci Rep. 2024; 14(1): 21839 Doi: 10.1038/s41598-024-72748-7 [OPEN ACCESS]
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Joham, SJ; Hadzic, A; Urschler, M Implicit Is Not Enough: Explicitly Enforcing Anatomical Priors inside Landmark Localization Models.
Bioengineering (Basel). 2024; 11(9): Doi: 10.3390/bioengineering11090932 [OPEN ACCESS]
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Kugic, A; Martin, I; Modersohn, L; Pallaoro, P; Kreuzthaler, M; Schulz, S; Boeker, M Processing of Short-Form Content in Clinical Narratives: Systematic Scoping Review.
J Med Internet Res. 2024; 26:e57852 Doi: 10.2196/57852 [OPEN ACCESS]
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Mathian, E; Drouet, Y; Sexton-Oates, A; Papotti, M; Pelosi, G; Vignaud, JM; Brcic, L; Mansuet-Lupo, A; Acala, N; Fernandez-Cuesta, L; Lantuejoul, S; Foll, M Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumors in the lungNENomics project
J NEUROENDOCRINOL. 2024; 36: 34-34. [Poster]
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Mathian, É; Drouet, Y; Sexton-Oates, A; Papotti, MG; Pelosi, G; Vignaud, JM; Brcic, L; Mansuet-Lupo, A; Damiola, F; Altun, C; Berthet, JP; Fournier, CB; Brustugun, OT; Centonze, G; Chalabreysse, L; de, Montpréville, VT; di, Micco, CM; Fadel, E; Gadot, N; Graziano, P; Hofman, P; Hofman, V; Lacomme, S; Lund-Iversen, M; Mangiante, L; Milione, M; Muscarella, LA; Perrin, C; Planchard, G; Popper, H; Rousseau, N; Roz, L; Sabella, G; Tabone-Eglinger, S; Voegele, C; Volante, M; Walter, T; Dingemans, AM; Moonen, L; Speel, EJ; Derks, J; Girard, N; Chen, L; Alcala, N; Fernandez-Cuesta, L; Lantuejoul, S; Foll, M Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumours in the lungNENomics project.
ESMO Open. 2024; 9(6):103591 Doi: 10.1016/j.esmoop.2024.103591 [OPEN ACCESS]
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Meisenzahl, C; Gillette, K; Prassl, AJ; Plank, G; Sapp, JL; Wang, L BOATMAP: Bayesian Optimization Active Targeting for Monomorphic Arrhythmia Pace-mapping.
Comput Biol Med. 2024; 182:109201 Doi: 10.1016/j.compbiomed.2024.109201 [OPEN ACCESS]
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Moser, P; Reishofer, G; Prückl, R; Schaffelhofer, S; Freigang, S; Thumfart, S; Mahdy, Ali, K Real-time estimation of the optimal coil placement in transcranial magnetic stimulation using multi-task deep learning.
Sci Rep. 2024; 14(1): 19361 Doi: 10.1038/s41598-024-70367-w [OPEN ACCESS]
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Sackl, M; Tinauer, C; Urschler, M; Enzinger, C; Stollberger, R; Ropele, S Fully Automated Hippocampus Segmentation using T2-informed Deep Convolutional Neural Networks.
Neuroimage. 2024; 298: 120767 Doi: 10.1016/j.neuroimage.2024.120767
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Saranti, A; Pfeifer, B; Gollob, C; Stampfer, K; Holzinger, A From 3D point-cloud data to explainable geometric deep learning: State-of-the-art and future challenges
WIRES DATA MIN KNOWL. 2024; Doi: 10.1002/widm.1554
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2023

Buchner, JA; Peeken, JC; Etzel, L; Ezhov, I; Mayinger, M; Christ, SM; Brunner, TB; Wittig, A; Menze, BH; Zimmer, C; Meyer, B; Guckenberger, M; Andratschke, N; El, Shafie, RA; Debus, J; Rogers, S; Riesterer, O; Schulze, K; Feldmann, HJ; Blanck, O; Zamboglou, C; Ferentinos, K; Bilger, A; Grosu, AL; Wolff, R; Kirschke, JS; Eitz, KA; Combs, SE; Bernhardt, D; Rueckert, D; Piraud, M; Wiestler, B; Kofler, F Identifying core MRI sequences for reliable automatic brain metastasis segmentation.
Radiother Oncol. 2023; 188: 109901 Doi: 10.1016/j.radonc.2023.109901
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Cognolato, F; O'Brien, K; Jin, J; Robinson, S; Laun, FB; Barth, M; Bollmann, S NeXtQSM-A complete deep learning pipeline for data-consistent Quantitative Susceptibility Mapping trained with hybrid data
MED IMAGE ANAL. 2023; 84: 102700 Doi: 10.1016/j.media.2022.102700
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Evans, TE; Knol, MJ; Schwingenschuh, P; Wittfeld, K; Hilal, S; Ikram, MA; Dubost, F; van, Wijnen, KMH; Katschnig, P; Yilmaz, P; de, Bruijne, M; Habes, M; Chen, C; Langer, S; Völzke, H; Ikram, MK; Grabe, HJ; Schmidt, R; Adams, HHH; Vernooij, MW Determinants of Perivascular Spaces in the General Population: A Pooled Cohort Analysis of Individual Participant Data.
Neurology. 2023; 100(2):e107-e122 Doi: 10.1212/WNL.0000000000201349 [OPEN ACCESS]
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Holzinger, A; Keiblinger, K; Holub, P; Zatloukal, K; Müller, H AI for life: Trends in artificial intelligence for biotechnology.
NEW BIOTECHNOL. 2023; 74: 16-24. Doi: 10.1016/j.nbt.2023.02.001
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Jantscher, M; Gunzer, F; Kern, R; Hassler, E; Tschauner, S; Reishofer, G Information extraction from German radiological reports for general clinical text and language understanding.
Sci Rep. 2023; 13(1): 2353 Doi: 10.1038/s41598-023-29323-3 [OPEN ACCESS]
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Kerestes, R; Laansma, MA; Owens-Walton, C; Perry, A; van, Heese, EM; Al-Bachari, S; Anderson, TJ; Assogna, F; Aventurato, ÍK; van, Balkom, TD; Berendse, HW; van, den, Berg, KRE; Betts, R; Brioschi, R; Carr, J; Cendes, F; Clark, LR; Dalrymple-Alford, JC; Dirkx, MF; Druzgal, J; Durrant, H; Emsley, HCA; Garraux, G; Haroon, HA; Helmich, RC; van, den, Heuvel, OA; João, RB; Johansson, ME; Khachatryan, SG; Lochner, C; McMillan, CT; Melzer, TR; Mosley, PE; Newman, B; Opriessnig, P; Parkes, LM; Pellicano, C; Piras, F; Pitcher, TL; Poston, KL; Rango, M; Roos, A; Rummel, C; Schmidt, R; Schwingenschuh, P; Silva, LS; Smith, V; Squarcina, L; Stein, DJ; Tavadyan, Z; Tsai, CC; Vecchio, D; Vriend, C; Wang, JJ; Wiest, R; Yasuda, CL; Young, CB; Jahanshad, N; Thompson, PM; van, der, Werf, YD; Harding, IH, , ENIGMA-Parkinson's, Study Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study.
Mov Disord. 2023; 38(12):2269-2281 Doi: 10.1002/mds.29611 [OPEN ACCESS]
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Kommoss, KS; Winkler, JK; Mueller-Christmann, C; Bardehle, F; Toberer, F; Stolz, W; Kraenke, T; Hofmann-Wellenhof, R; Blum, A; Enk, A; Rosenberger, A; Haenssle, HA Observational study investigating the level of support from a convolutional neural network in face and scalp lesions deemed diagnostically 'unclear' by dermatologists.
Eur J Cancer. 2023; 185: 53-60. Doi: 10.1016/j.ejca.2023.02.025
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Lami, K; Ota, N; Yamaoka, S; Bychkov, A; Matsumoto, K; Uegami, W; Munkhdelger, J; Seki, K; Sukhbaatar, O; Attanoos, R; Berezowska, S; Brcic, L; Cavazza, A; English, JC; Fabro, AT; Ishida, K; Kashima, Y; Kitamura, Y; Larsen, BT; Marchevsky, AM; Miyazaki, T; Morimoto, S; Ozasa, M; Roden, AC; Schneider, F; Smith, ML; Tabata, K; Takano, AM; Tanaka, T; Tsuchiya, T; Nagayasu, T; Sakanashi, H; Fukuoka, J Standardized Classification of Lung Adenocarcinoma Subtypes and Improvement of Grading Assessment Through Deep Learning.
Am J Pathol. 2023; 193(12):2066-2079 Doi: 10.1016/j.ajpath.2023.07.002
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Lara-Hernandez, A; Rienmuller, T; Juarez, I; Perez, M; Reyna, F; Baumgartner, D; Makarenko, VN; Bockeria, OL; Maksudov, M; Rienmuller, R; Baumgartner, C Deep Learning-Based Image Registration in Dynamic Myocardial Perfusion CT Imaging
IEEE T MED IMAGING. 2023; 42(3): 684-696. Doi: 10.1109/TMI.2022.3214380
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L'Imperio, V; Wulczyn, E; Plass, M; Müller, H; Tamini, N; Gianotti, L; Zucchini, N; Reihs, R; Corrado, GS; Webster, DR; Peng, LH; Chen, PC; Lavitrano, M; Liu, Y; Steiner, DF; Zatloukal, K; Pagni, F Pathologist Validation of a Machine Learning-Derived Feature for Colon Cancer Risk Stratification.
JAMA Netw Open. 2023; 6(3): e2254891 Doi: 10.1001/jamanetworkopen.2022.54891 [OPEN ACCESS]
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Monaci, S; Qian, S; Gillette, K; Puyol-Antón, E; Mukherjee, R; Elliott, MK; Whitaker, J; Rajani, R; O'Neill, M; Rinaldi, CA; Plank, G; King, AP; Bishop, MJ Non-invasive localization of post-infarct ventricular tachycardia exit sites to guide ablation planning: a computational deep learning platform utilizing the 12-lead electrocardiogram and intracardiac electrograms from implanted devices.
Europace. 2023; 25(2):469-477 Doi: 10.1093/europace/euac178 [OPEN ACCESS]
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Schulz, S; Abdulnazar, A; Kreuzthaler, M Clustering Similar Diagnosis Terms.
Stud Health Technol Inform. 2023; 302: 837-838. Doi: 10.3233/SHTI230284
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2022

Egger, J; Gsaxner, C; Pepe, A; Pomykala, KL; Jonske, F; Kurz, M; Li, JN; Kleesiek, J Medical deep learning-A systematic meta-review
COMPUT METH PROG BIO. 2022; 221: 106874 Doi: 10.1016/j.cmpb.2022.106874
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Güllmar, D; Jacobsen, N; Deistung, A; Timmann, D; Ropele, S; Reichenbach, JR Investigation of biases in convolutional neural networks for semantic segmentation using performance sensitivity analysis.
Z Med Phys. 2022; 32(3): 346-360. Doi: 10.1016/j.zemedi.2021.11.004 [OPEN ACCESS]
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Herrera, CR; Grandits, T; Plank, G; Perdikaris, P; Costabal, FS; Pezzuto, S Physics-informed neural networks to learn cardiac fiber orientation from multiple electroanatomical maps
ENG COMPUT-GERMANY. 2022; Doi: 10.1007/s00366-022-01709-3
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Kau, T; Ziurlys, M; Taschwer, M; Kloss-Brandstätter, A; Grabner, G; Deutschmann, H FDA-approved deep learning software application versus radiologists with different levels of expertise: detection of intracranial hemorrhage in a retrospective single-center study.
Neuroradiology. 2022; Doi: 10.1007/s00234-021-02874-w
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Kirnbauer, B; Hadzic, A; Jakse, N; Bischof, H; Stern, D Automatic Detection of Periapical Osteolytic Lesions on Cone-beam Computed Tomography Using Deep Convolutional Neuronal Networks.
J Endod. 2022; 48(11):1434-1440 Doi: 10.1016/j.joen.2022.07.013
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Lu, AX; Lu, AX; Pritišanac, I; Zarin, T; Forman-Kay, JD; Moses, AM Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning.
PLoS Comput Biol. 2022; 18(6): e1010238 Doi: 10.1371/journal.pcbi.1010238 [OPEN ACCESS]
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Milling, M; Baird, A; Bartl-Pokorny, KD; Liu, S; Alcorn, AM; Shen, J; Tavassoli, T; Ainger, E; Pellicano, E; Pantic, M; Cummins, N; Schuller, BW Evaluating the Impact of Voice Activity Detection on Speech Emotion Recognition for Autistic Children
FRONT COMP SCI-SWITZ. 2022; 4: 837269 Doi: 10.3389/fcomp.2022.837269
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Milling, M; Pokorny, FB; Bartl-Pokorny, KD; Schuller, BW Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell.
Front Digit Health. 2022; 4: 886615 Doi: 10.3389/fdgth.2022.886615 [OPEN ACCESS]
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Müller, H; Holzinger, A; Plass, M; Brcic, L; Stumptner, C; Zatloukal, K Explainability and causability for artificial intelligence-supported medical image analysis in the context of the European In Vitro Diagnostic Regulation.
N Biotechnol. 2022; 70:67-72 Doi: 10.1016/j.nbt.2022.05.002
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Oner, D; Kozinski, M; Citraro, L; Fua, P Adjusting the Ground Truth Annotations for Connectivity-Based Learning to Delineate.
IEEE Trans Med Imaging. 2022; 41(12): 3675-3685. Doi: 10.1109/TMI.2022.3193072
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Pfeifer, B; Saranti, A; Holzinger, A GNN-SubNet: disease subnetwork detection with explainable graph neural networks.
Bioinformatics. 2022; 38(Supplement_2): ii120-ii126. Doi: 10.1093/bioinformatics/btac478
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Radl, L; Jin, Y; Pepe, A; Li, J; Gsaxner, C; Zhao, FH; Egger, J AVT: Multicenter aortic vessel tree CTA dataset collection with ground truth segmentation masks.
Data Brief. 2022; 40:107801 Doi: 10.1016/j.dib.2022.107801 [OPEN ACCESS]
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Siegerist, F; Hay, E; Dikou, JS; Pollheimer, M; Büscher, A; Oh, J; Ribback, S; Zimmermann, U; Bräsen, JH; Lenoir, O; Drenic, V; Eller, K; Tharaux, PL; Endlich, N ScoMorphoFISH: A deep learning enabled toolbox for single-cell single-mRNA quantification and correlative (ultra-)morphometry.
J Cell Mol Med. 2022; 26(12): 3513-3526. Doi: 10.1111/jcmm.17392 [OPEN ACCESS]
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Sorantin, E; Grasser, MG; Hemmelmayr, A; Tschauner, S; Hrzic, F; Weiss, V; Lacekova, J; Holzinger, A The augmented radiologist: artificial intelligence in the practice of radiology.
Pediatr Radiol. 2022; 52(11):2074-2086 Doi: 10.1007/s00247-021-05177-7 [OPEN ACCESS]
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2021

Bao, X; Shi, R; Zhao, T; Wang, Y; Anastasov, N; Rosemann, M; Fang, W Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC.
Cancer Immunol Immunother. 2021; 70(1): 189-202. Doi: 10.1007/s00262-020-02669-7 [OPEN ACCESS]
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Bilgic, B; Langkammer, C; Marques, JP; Meineke, J; Milovic, C; Schweser, F, , QSM, Challenge, 2.0, Organization, Committee QSM reconstruction challenge 2.0: Design and report of results.
Magn Reson Med. 2021; 86(3):1241-1255 Doi: 10.1002/mrm.28754 [OPEN ACCESS]
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Diouri, O; Cigler, M; Vettoretti, M; Mader, JK; Choudhary, P; Renard, E, , HYPO-RESOLVE, Consortium Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments.
Diabetes Metab Res Rev. 2021; e3449 Doi: 10.1002/dmrr.3449 [OPEN ACCESS]
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