Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Publikationen
Suchbegriffe: ARTIFICIAL INTELLIGENCE, . Treffer: 71
2023
Berger, MF; Winter, R; Tuca, AC; Michelitsch, B; Schenkenfelder, B; Hartmann, R; Giretzlehner, M; Reishofer, G; Kamolz, LP; Lumenta, DB
Workflow assessment of an augmented reality application for planning of perforator flaps in plastic reconstructive surgery: Game or game changer?
Digit Health. 2023; 9:20552076231173554
Doi: 10.1177/20552076231173554
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Carrington, AM; Manuel, DG; Fieguth, PW; Ramsay, T; Osmani, V; Wernly, B; Bennett, C; Hawken, S; Magwood, O; Sheikh, Y; McInnes, M; Holzinger, A
Deep ROC Analysis and AUC as Balanced Average Accuracy, for Improved Classifier Selection, Audit and Explanation
IEEE T PATTERN ANAL. 2023; 45(1): 329-341.
Doi: 10.1109/TPAMI.2022.3145392
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Dimai, HP
New Horizons: Artificial Intelligence Tools for Managing Osteoporosis
J CLIN ENDOCR METAB. 2023;
Doi: 10.1210/clinem/dgac702
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Holzinger, A; Keiblinger, K; Holub, P; Zatloukal, K; Müller, H
AI for life: Trends in artificial intelligence for biotechnology.
N Biotechnol. 2023; 74:16-24
Doi: 10.1016/j.nbt.2023.02.001
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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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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
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Litscher, G
The Future of Laser Acupuncture-Robot-Assisted Laser Stimulation and Evaluation.
Life (Basel). 2023; 13(1): 96
Doi: 10.3390/life13010096
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Marschik, PB; Kulvicius, T; Flügge, S; Widmann, C; Nielsen-Saines, K; Schulte-Rüther, M; Hüning, B; Bölte, S; Poustka, L; Sigafoos, J; Wörgötter, F; Einspieler, C; Zhang, D
Open video data sharing in developmental science and clinical practice.
iScience. 2023; 26(4): 106348
Doi: 10.1016/j.isci.2023.106348
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Plass, M; Kargl, M; Kiehl, TR; Regitnig, P; Geissler, C; Evans, T; Zerbe, N; Carvalho, R; Holzinger, A; Muller, H
Explainability and causability in digital pathology
J PATHOL CLIN RES. 2023;
Doi: 10.1002/cjp2.322
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Schnabel, RB; Marinelli, EA; Arbelo, E; Boriani, G; Boveda, S; Buckley, CM; Camm, AJ; Casadei, B; Chua, W; Dagres, N; de, Melis, M; Desteghe, L; Diederichsen, SZ; Duncker, D; Eckardt, L; Eisert, C; Engler, D; Fabritz, L; Freedman, B; Gillet, L; Goette, A; Guasch, E; Svendsen, JH; Hatem, SN; Haeusler, KG; Healey, JS; Heidbuchel, H; Hindricks, G; Hobbs, FDR; Hübner, T; Kotecha, D; Krekler, M; Leclercq, C; Lewalter, T; Lin, H; Linz, D; Lip, GYH; Løchen, ML; Lucassen, W; Malaczynska-Rajpold, K; Massberg, S; Merino, JL; Meyer, R; Mont, L; Myers, MC; Neubeck, L; Niiranen, T; Oeff, M; Oldgren, J; Potpara, TS; Psaroudakis, G; Pürerfellner, H; Ravens, U; Rienstra, M; Rivard, L; Scherr, D; Schotten, U; Shah, D; Sinner, MF; Smolnik, R; Steinbeck, G; Steven, D; Svennberg, E; Thomas, D; True, Hills, M; van, Gelder, IC; Vardar, B; Palà, E; Wakili, R; Wegscheider, K; Wieloch, M; Willems, S; Witt, H; Ziegler, A; Daniel, Zink, M; Kirchhof, P
Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference.
Europace. 2023; 25(1):6-27
Doi: 10.1093/europace/euac062
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Smolle, MA; Goetz, C; Maurer, D; Vielgut, I; Novak, M; Zier, G; Leithner, A; Nehrer, S; Paixao, T; Ljuhar, R; Sadoghi, P
Artificial intelligence-based computer-aided system for knee osteoarthritis assessment increases experienced orthopaedic surgeons' agreement rate and accuracy.
Knee Surg Sports Traumatol Arthrosc. 2023; 31(3):1053-1062
Doi: 10.1007/s00167-022-07220-y
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2022
Bertsimas, D; Margonis, GA; Sujichantararat, S; Boerner, T; Ma, Y; Wang, J; Kamphues, C; Sasaki, K; Tang, S; Gagniere, J; Dupré, A; Løes, IM; Wagner, D; Stasinos, G; Macher-Beer, A; Burkhart, R; Morioka, D; Imai, K; Ardiles, V; O'Connor, JM; Pawlik, TM; Poultsides, G; Seeliger, H; Beyer, K; Kaczirek, K; Kornprat, P; Aucejo, FN; de, Santibañes, E; Baba, H; Endo, I; Lønning, PE; Kreis, ME; Weiss, MJ; Wolfgang, CL; D'Angelica, M
Using Artificial Intelligence to Find the Optimal Margin Width in Hepatectomy for Colorectal Cancer Liver Metastases.
JAMA Surg. 2022; 157(8): e221819
Doi: 10.1001/jamasurg.2022.1819
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Betz-Stablein, B; D'Alessandro, B; Koh, U; Plasmeijer, E; Janda, M; Menzies, SW; Hofmann-Wellenhof, R; Green, AC; Soyer, HP
Reproducible Naevus Counts Using 3D Total Body Photography and Convolutional Neural Networks
DERMATOLOGY. 2021;
Doi: 10.1159/000517218
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Brunt, EM; Clouston, AD; Goodman, Z; Guy, C; Kleiner, DE; Lackner, C; Tiniakos, DG; Wee, A; Yeh, M; Leow, WQ; Chng, E; Ren, YY; Bee, GGB; Powell, EE; Rinella, M; Sanyal, AJ; Neuschwander-Tetri, B; Younossi, Z; Charlton, M; Ratziu, V; Harrison, SA; Tai, DA; Anstee, QM
Complexity of ballooned hepatocyte feature recognition: Defining a training atlas for artificial intelligence-based imaging in NAFLD
J HEPATOL. 2022; 76(5): 1030-1041.
Doi: 10.1016/j.jhep.2022.01.011
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Chalopin, C; Nickel, F; Pfahl, A; Köhler, H; Maktabi, M; Thieme, R; Sucher, R; Jansen-Winkeln, B; Studier-Fischer, A; Seidlitz, S; Maier-Hein, L; Neumuth, T; Melzer, A; Müller-Stich, BP; Gockel, I
[Artificial intelligence and hyperspectral imaging for image-guided assistance in minimally invasive surgery].
Chirurgie (Heidelb). 2022; 93(10): 940-947.
Doi: 10.1007/s00104-022-01677-w
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Combi, C; Amico, B; Bellazzi, R; Holzinger, A; Moore, JH; Zitnik, M; Holmes, JH
A manifesto on explainability for artificial intelligence in medicine.
Artif Intell Med. 2022; 133:102423
Doi: 10.1016/j.artmed.2022.102423
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Evans, T; Retzlaff, CO; Geissler, C; Kargl, M; Plass, M; Muller, H; Kiehl, TR; Zerbe, N; Holzinger, A
The explainability paradox: Challenges for xAI in digital pathology
FUTURE GENER COMP SY. 2022; 133: 281-296.
Doi: 10.1016/j.future.2022.03.009
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Faihs, L; Firouz, B; Slezak, P; Slezak, C; Weissensteiner, M; Ebner, T; Tabrizi-Wizsy, NG; Schicho, K; Dungel, P
A Novel Artificial Intelligence-Based Approach for Quantitative Assessment of Angiogenesis in the Ex Ovo CAM Model
CANCERS. 2022; 14(17): 4273
Doi: 10.3390/cancers14174273
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Feng, S; Liu, Q; Patel, A; Bazai, SU; Jin, CK; Kim, JS; Sarrafzadeh, M; Azzollini, D; Yeoh, J; Kim, E; Gordon, S; Jang-Jaccard, J; Urschler, M; Barnard, S; Fong, A; Simmers, C; Tarr, GP; Wilson, B
Automated pneumothorax triaging in chest X-rays in the New Zealand population using deep-learning algorithms.
J Med Imaging Radiat Oncol. 2022; 66(8): 1035-1043.
Doi: 10.1111/1754-9485.13393
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Fusar-Poli, P; Manchia, M; Koutsouleris, N; Leslie, D; Woopen, C; Calkins, ME; Dunn, M; Tourneau, CL; Mannikko, M; Mollema, T; Oliver, D; Rietschel, M; Reininghaus, EZ; Squassina, A; Valmaggia, L; Kessing, LV; Vieta, E; Correll, CU; Arango, C; Andreassen, OA, , PSMD, EBRA, cluster, (annex, 1)
Ethical considerations for precision psychiatry: A roadmap for research and clinical practice.
Eur Neuropsychopharmacol. 2022; 63: 17-34.
Doi: 10.1016/j.euroneuro.2022.08.001
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Geisler, A; Schmidt, A; Branzan, D
[Digital Patient Data, Artificial Intelligence and Machine Learning in the New Era of Endovascular Aortic Therapies].
Zentralbl Chir. 2022; 147(5): 432-438.
Doi: 10.1055/a-1938-8227
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Gunzer, F; Jantscher, M; Hassler, EM; Kau, T; Reishofer, G
Reproducibility of artificial intelligence models in computed tomography of the head: a quantitative analysis.
Insights Imaging. 2022; 13(1):173
Doi: 10.1186/s13244-022-01311-7
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Holzinger, A; Dehmer, M; Emmert-Streib, F; Cucchiara, R; Augenstein, I; Del Ser, J; Samek, W; Jurisica, I; Diaz-Rodriguez, N
Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence
INFORM FUSION. 2022; 79: 263-278.
Doi: 10.1016/j.inffus.2021.10.007
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Holzinger, A; Kargl, M; Kipperer, B; Regitnig, P; Plass, M; Muller, H
Personas for Artificial Intelligence (AI) an Open Source Toolbox
IEEE ACCESS. 2022; 10: 23732-23747.
Doi: 10.1109/ACCESS.2022.3154776
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Homeyer, A; Geißler, C; Schwen, LO; Zakrzewski, F; Evans, T; Strohmenger, K; Westphal, M; Bülow, RD; Kargl, M; Karjauv, A; Munné-Bertran, I; Retzlaff, CO; Romero-López, A; Sołtysiński, T; Plass, M; Carvalho, R; Steinbach, P; Lan, YC; Bouteldja, N; Haber, D; Rojas-Carulla, M; Vafaei, Sadr, A; Kraft, M; Krüger, D; Fick, R; Lang, T; Boor, P; Müller, H; Hufnagl, P; Zerbe, N
Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology.
Mod Pathol. 2022; 35(12):1759-1769
Doi: 10.1038/s41379-022-01147-y
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Janisch, M; Apfaltrer, G; Hržić, F; Castellani, C; Mittl, B; Singer, G; Lindbichler, F; Pilhatsch, A; Sorantin, E; Tschauner, S
Pediatric radius torus fractures in x-rays-how computer vision could render lateral projections obsolete.
Front Pediatr. 2022; 10: 1005099
Doi: 10.3389/fped.2022.1005099
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Kargl, M; Plass, M; Müller, H
A Literature Review on Ethics for AI in Biomedical Research and Biobanking.
Yearb Med Inform. 2022; 31(1): 152-160.
Doi: 10.1055/s-0042-1742516
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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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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
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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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Nagy, E; Marterer, R; Hržić, F; Sorantin, E; Tschauner, S
Learning rate of students detecting and annotating pediatric wrist fractures in supervised artificial intelligence dataset preparations.
PLoS One. 2022; 17(10): e0276503
Doi: 10.1371/journal.pone.0276503
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Plass, M; Kargl, M; Nitsche, P; Jungwirth, E; Holzinger, A; Muller, H
Understanding and Explaining Diagnostic Paths: Towards Augmented Decision Making.
IEEE Comput Graph Appl. 2022; PP:
Doi: 10.1109/MCG.2022.3197957
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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
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Zandonella, Callegher, S; Giovannini, I; Zenz, S; Manfrè, V; Stradner, MH; Hocevar, A; Gutierrez, M; Quartuccio, L; De, Vita, S; Zabotti, A
Sjögren syndrome: looking forward to the future.
Ther Adv Musculoskelet Dis. 2022; 14: 1759720X221100295
Doi: 10.1177/1759720X221100295
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2021
Bertsimas, D; Margonis, GA; Huang, Y; Andreatos, N; Wiberg, H; Ma, Y; Mcintyre, C; Pulvirenti, A; Wagner, D; van, Dam, JL; Gavazzi, F; Buettner, S; Imai, K; Stasinos, G; He, J; Kamphues, C; Beyer, K; Seeliger, H; Weiss, MJ; Kreis, M; Cameron, JL; Wei, AC; Kornprat, P; Baba, H; Koerkamp, BG; Zerbi, A; D'Angelica, M; Wolfgang, CL
Toward an Optimized Staging System for Pancreatic Ductal Adenocarcinoma: A Clinically Interpretable, Artificial Intelligence-Based Model.
JCO Clin Cancer Inform. 2021; 5: 1220-1231.
Doi: 10.1200/CCI.21.00001
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Giovannini, I; Bosch, P; Dejaco, C; De, Marco, G; McGonagle, D; Quartuccio, L; De, Vita, S; Errichetti, E; Zabotti, A
The Digital Way to Intercept Psoriatic Arthritis.
FRONT MED-LAUSANNE. 2021; 8: 792972
Doi: 10.3389/fmed.2021.792972
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Gockel, I; Barberio, M; Diana, M; Thieme, R; Pfahl, A; Sucher, R; Köhler, H; Chalopin, C; Maktabi, M; Jansen-Winkeln, B
[New intraoperative fluorescence-based and spectroscopic imaging techniques in visceral medicine - precision surgery in the "high tech"-operating room].
Z Gastroenterol. 2021; 59(7):683-690
Doi: 10.1055/a-1481-1993
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Hržić, F; Žužić, I; Tschauner, S; Štajduhar, I
Cast suppression in radiographs by generative adversarial networks.
J Am Med Inform Assoc. 2021; 28(12):2687-2694
Doi: 10.1093/jamia/ocab192
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Hussain, S; Raza, Z; Kumar, TVV; Goswami, N
Diagnosing Neurally Mediated Syncope Using Classification Techniques.
J Clin Med. 2021; 10(21):
Doi: 10.3390/jcm10215016
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Jean-Quartier, C; Jeanquartier, F; Ridvan, A; Kargl, M; Mirza, T; Stangl, T; Markaĉ, R; Jurada, M; Holzinger, A
Mutation-based clustering and classification analysis reveals distinctive age groups and age-related biomarkers for glioma.
BMC MED INFORM DECIS. 2021; 21(1): 77-77.
Doi: 10.1186/s12911-021-01420-1
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Karami, H; Derakhshani, A; Ghasemigol, M; Fereidouni, M; Miri-Moghaddam, E; Baradaran, B; Tabrizi, NJ; Najafi, S; Solimando, AG; Marsh, LM; Silvestris, N; De, Summa, S; Paradiso, AV; Racanelli, V; Safarpour, H
Weighted Gene Co-Expression Network Analysis Combined with Machine Learning Validation to Identify Key Modules and Hub Genes Associated with SARS-CoV-2 Infection.
J Clin Med. 2021; 10(16):
Doi: 10.3390/jcm10163567
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Koromani, F; Alonso, N; Alves, I; Brandi, ML; Foessl, I; Formosa, MM; Morgenstern, MF; Karasik, D; Kolev, M; Makitie, O; Ntzani, E; Pietsch, BO; Ohlsson, C; Rauner, M; Soe, K; Soldatovic, I; Teti, A; Valjevac, A; Rivadeneira, F
The "GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork": Origins, Rationale, Organization, and Prospects.
Front Endocrinol (Lausanne). 2021; 12:709815
Doi: 10.3389/fendo.2021.709815
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Majnarić, LT; Babič, F; O'Sullivan, S; Holzinger, A
AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity.
J CLIN MED. 2021; 10(4): 766
Doi: 10.3390/jcm10040766
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Memon, AR; Li, JN; Egger, J; Chen, XJ
A review on patient-specific facial and cranial implant design using Artificial Intelligence (AI) techniques
EXPERT REV MED DEVIC. 2021;
Doi: 10.1080/17434440.2021.1969914
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Mrazek, C; Haschke-Becher, E; Felder, TK; Keppel, MH; Oberkofler, H; Cadamuro, J
Laboratory Demand Management Strategies-An Overview.
Diagnostics (Basel). 2021; 11(7):
Doi: 10.3390/diagnostics11071141
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Nehrer, S; Ljuhar, R; Steindl, P; Simon, R; Maurer, D; Ljuhar, D; Bertalan, Z; Dimai, HP; Goetz, C; Paixao, T
Automated Knee Osteoarthritis Assessment Increases Physicians' Agreement Rate and Accuracy: Data from the Osteoarthritis Initiative.
Cartilage. 2021; 13(1_suppl):957S-965S
Doi: 10.1177/1947603519888793
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Overhoff, D; Kohlmann, P; Frydrychowicz, A; Gatidis, S; Loewe, C; Moltz, J; Kuhnigk, JM; Gutberlet, M; Winter, H; Völker, M; Hahn, H; Schoenberg, SO, , Vorstandskommission, Radiomics, und, Big, data:;Vorstand, der, Deutschen, Röntgengesellschaft:;Präsidium, der, Österreichischen, Röntgengesellschaft:
The International Radiomics Platform - An Initiative of the German and Austrian Radiological Societies - First Application Examples.
Rofo. 2021; 193(3): 276-288.
Doi: 10.1055/a-1244-2775
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Ranjan, R; Partl, R; Erhart, R; Kurup, N; Schnidar, H
The mathematics of erythema: Development of machine learning models for artificial intelligence assisted measurement and severity scoring of radiation induced dermatitis.
Comput Biol Med. 2021; 139:104952
Doi: 10.1016/j.compbiomed.2021.104952
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Reich, O; Pickel, H
100 years of iodine testing of the cervix: A critical review and implications for the future
EUR J OBSTET GYN R B. 2021; 261: 34-40.
Doi: 10.1016/j.ejogrb.2021.04.011
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