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


Suchbegriffe: LEARNING ALGORITHM, . Treffer: 22


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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De Leon, G; Frohlich, E; Fink, E; Di Pizio, A; Salar-Behzadi, S Premexotac: Machine learning bitterants predictor for advancing pharmaceutical development
INT J PHARMACEUT. 2022; 628: 122263 Doi: 10.1016/j.ijpharm.2022.122263
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Jurmeister, P; Leitheiser, M; Wolkenstein, P; Klauschen, F; Capper, D; Brcic, L DNA methylation-based machine learning classification distinguishes pleural mesothelioma from chronic pleuritis, pleural carcinosis, and pleomorphic lung carcinomas.
Lung Cancer. 2022; 170:105-113 Doi: 10.1016/j.lungcan.2022.06.008
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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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Hržić, F; Tschauner, S; Sorantin, E; Štajduhar, I XAOM: A method for automatic alignment and orientation of radiographs for computer-aided medical diagnosis.
Comput Biol Med. 2021; 132:104300 Doi: 10.1016/j.compbiomed.2021.104300
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Reich, S; Zhang, D; Kulvicius, T; Bölte, S; Nielsen-Saines, K; Pokorny, FB; Peharz, R; Poustka, L; Wörgötter, F; Einspieler, C; Marschik, PB Novel AI driven approach to classify infant motor functions.
Sci Rep. 2021; 11(1): 9888-9888. Doi: 10.1038/s41598-021-89347-5 [OPEN ACCESS]
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Abdel-Aziz, MI; Brinkman, P; Vijverberg, SJH; Neerincx, AH; de, Vries, R; Dagelet, YWF; Riley, JH; Hashimoto, S; Montuschi, P; Chung, KF; Djukanovic, R; Fleming, LJ; Murray, CS; Frey, U; Bush, A; Singer, F; Hedlin, G; Roberts, G; Dahlén, SE; Adcock, IM; Fowler, SJ; Knipping, K; Sterk, PJ; Kraneveld, AD; Maitland-van, der, Zee, AH, , U-BIOPRED, Study, Group;Amsterdam, UMC, Breath, Research, Group eNose breath prints as a surrogate biomarker for classifying patients with asthma by atopy.
J Allergy Clin Immunol. 2020; 146(5):1045-1055 Doi: 10.1016/j.jaci.2020.05.038
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Braun, T; Spiliopoulos, S; Veltman, C; Hergesell, V; Passow, A; Tenderich, G; Borggrefe, M; Koerner, MM Detection of myocardial ischemia due to clinically asymptomatic coronary artery stenosis at rest using supervised artificial intelligence-enabled vectorcardiography - A five-fold cross validation of accuracy.
J Electrocardiol. 2020; 59(5):100-105 Doi: 10.1016/j.jelectrocard.2019.12.018
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Galateau Salle, F; Le Stang, N; Tirode, F; Courtiol, P; Nicholson, AG; Tsao, MS; Tazelaar, HD; Churg, A; Dacic, S; Roggli, V; Pissaloux, D; Maussion, C; Moarii, M; Beasley, MB; Begueret, H; Chapel, DB; Copin, MC; Gibbs, AR; Klebe, S; Lantuejoul, S; Nabeshima, K; Vignaud, JM; Attanoos, R; Brcic, L; Capron, F; Chirieac, LR; Damiola, F; Sequeiros, R; Cazes, A; Damotte, D; Foulet, A; Giusiano-Courcambeck, S; Hiroshima, K; Hofman, V; Husain, AN; Kerr, K; Marchevsky, A; Paindavoine, S; Picquenot, JM; Rouquette, I; Sagan, C; Sauter, J; Thivolet, F; Brevet, M; Rouvier, P; Travis, WD; Planchard, G; Weynand, B; Clozel, T; Wainrib, G; Fernandez-Cuesta, L; Pairon, JC; Rusch, V; Girard, N Comprehensive Molecular and Pathologic Evaluation of Transitional Mesothelioma Assisted by Deep Learning Approach: A Multi-Institutional Study of the International Mesothelioma Panel from the MESOPATH Reference Center.
J Thorac Oncol. 2020; 15(6):1037-1053 Doi: 10.1016/j.jtho.2020.01.025 [OPEN ACCESS]
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Jauk, S; Kramer, D; Großauer, B; Rienmüller, S; Avian, A; Berghold, A; Leodolter, W; Schulz, S Risk prediction of delirium in hospitalized patients using machine learning: An implementation and prospective evaluation study.
J Am Med Inform Assoc. 2020; 27(9): 1383-1392. Doi: 10.1093/jamia/ocaa113 [OPEN ACCESS]
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Lienhart, AM; Kramer, D; Jauk, S; Gugatschka, M; Leodolter, W; Schlegl, T Multivariable Risk Prediction of Dysphagia in Hospitalized Patients Using Machine Learning.
Stud Health Technol Inform. 2020; 271: 31-38. Doi: 10.3233/SHTI200071
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Dimai, HP; Ljuhar, R; Ljuhar, D; Norman, B; Nehrer, S; Kurth, A; Fahrleitner-Pammer, A Assessing the effects of long-term osteoporosis treatment by using conventional spine radiographs: results from a pilot study in a sub-cohort of a large randomized controlled trial.
Skeletal Radiol. 2019; 48(7):1023-1032 Doi: 10.1007/s00256-018-3118-y [OPEN ACCESS]
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Tschandl, P; Codella, N; Akay, BN; Argenziano, G; Braun, RP; Cabo, H; Gutman, D; Halpern, A; Helba, B; Hofmann-Wellenhof, R; Lallas, A; Lapins, J; Longo, C; Malvehy, J; Marchetti, MA; Marghoob, A; Menzies, S; Oakley, A; Paoli, J; Puig, S; Rinner, C; Rosendahl, C; Scope, A; Sinz, C; Soyer, HP; Thomas, L; Zalaudek, I; Kittler, H Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study.
Lancet Oncol. 2019; 20(7):938-947 Doi: 10.1016/S1470-2045(19)30333-X [OPEN ACCESS]
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Veeranki, SPK; Kramer, D; Hayn, D; Jauk, S; Eggerth, A; Quehenberger, F; Leodolter, W; Schreier, G Is Regular Re-Training of a Predictive Delirium Model Necessary After Deployment in Routine Care?
Stud Health Technol Inform. 2019; 260: 186-191.


Wu, O; Winzeck, S; Giese, AK; Hancock, BL; Etherton, MR; Bouts, MJRJ; Donahue, K; Schirmer, MD; Irie, RE; Mocking, SJT; McIntosh, EC; Bezerra, R; Kamnitsas, K; Frid, P; Wasselius, J; Cole, JW; Xu, H; Holmegaard, L; Jiménez-Conde, J; Lemmens, R; Lorentzen, E; McArdle, PF; Meschia, JF; Roquer, J; Rundek, T; Sacco, RL; Schmidt, R; Sharma, P; Slowik, A; Stanne, TM; Thijs, V; Vagal, A; Woo, D; Bevan, S; Kittner, SJ; Mitchell, BD; Rosand, J; Worrall, BB; Jern, C; Lindgren, AG; Maguire, J; Rost, NS Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data.
Stroke. 2019; 50(7): 1734-1741. Doi: 10.1161/STROKEAHA.119.025373 [OPEN ACCESS]
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Jauk, S; Kramer, D; Schulz, S; Leodolter, W Evaluating the Impact of Incorrect Diabetes Coding on the Performance of Multivariable Prediction Models.
Stud Health Technol Inform. 2018; 251: 249-252.



Kramer, D; Veeranki, S; Hayn, D; Quehenberger, F; Leodolter, W; Jagsch, C; Schreier, G Development and Validation of a Multivariable Prediction Model for the Occurrence of Delirium in Hospitalized Gerontopsychiatry and Internal Medicine Patients.
Stud Health Technol Inform. 2017; 236:32-39



Wiltgen, M; Bloice, M; Koller, S; Hoffmann-Wellenhof, R; Smolle, J; Gerger, A Computer-aided diagnosis of melanocytic skin tumors by use of confocal laser scanning microscopy images.
Anal Quant Cytol Histol. 2011; 33(2):85-100
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Wiltgen, M; Tilz, GP Molecular diagnosis and prognosis with DNA microarrays.
Hematology. 2011; 16(3):166-176 Doi: 10.1179/102453311X12953015767257
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Leistritz, L; Galicki, M; Kochs, E; Zwick, EB; Fitzek, C; Reichenbach, JR; Witte, H Application of generalized dynamic neural networks to biomedical data.
IEEE Trans Biomed Eng. 2006; 53(11):2289-2299 Doi: 10.1109/TBME.2006.881766
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Galicki, M; Leistritz, L; Zwick, EB; Witte, H Improving generalization capabilities of dynamic neural networks.
Neural Comput. 2004; 16(6):1253-1282 Doi: 10.1162/089976604773717603
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Gerger, A; Pompl, R; Smolle, J; Wilhelm Stolz Automated epiluminescence microscopy--tissue counter analysis using CART and 1-NN in the diagnosis of Melanoma.
SKIN RES TECHNOL 2003 9: 105-110. Doi: 10.1034/j.1600-0846.2003.00028.x
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