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Inga Strümke
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Year
Science with e-ASTROGAM: A space mission for MeV–GeV gamma-ray astrophysics
A De Angelis, V Tatischeff, IA Grenier, J McEnery, M Mallamaci, M Tavani, ...
Journal of High Energy Astrophysics 19, 1-106, 2018
186*2018
Explaining deep neural networks for knowledge discovery in electrocardiogram analysis
SA Hicks, JL Isaksen, V Thambawita, J Ghouse, G Ahlberg, A Linneberg, ...
Scientific reports 11 (1), 1-11, 2021
182021
Shapley values for feature selection: The good, the bad, and the axioms
D Fryer, I Strümke, H Nguyen
IEEE Access 9, 144352-144360, 2021
142021
On evaluation metrics for medical applications of artificial intelligence
SA Hicks, I Strümke, V Thambawita, M Hammou, MA Riegler, P Halvorsen, ...
Scientific Reports 12 (1), 1-9, 2022
92022
Trilinear-augmented gaugino mediation
J Heisig, J Kersten, N Murphy, I Strümke
Journal of High Energy Physics 2017 (5), 1-21, 2017
82017
Signal mixture estimation for degenerate heavy Higgses using a deep neural network
A Kvellestad, S Maeland, I Strümke
The European Physical Journal C 78 (12), 1-11, 2018
72018
Explaining the data or explaining a model? Shapley values that uncover non-linear dependencies
DV Fryer, I Strümke, H Nguyen
arXiv preprint arXiv:2007.06011, 2020
52020
Shapley value confidence intervals for variable selection in regression models
D Fryer, I Strumke, H Nguyen
42020
Beyond Cuts in Small Signal Scenarios-Enhanced Sneutrino Detectability Using Machine Learning
D Alvestad, N Fomin, J Kersten, S Maeland, I Strümke
arXiv preprint arXiv:2108.03125, 2021
32021
ID: 3523524 DATA AUGMENTATION USING GENERATIVE ADVERSARIAL NETWORKS FOR CREATING REALISTIC ARTIFICIAL COLON POLYP IMAGES: VALIDATION STUDY BY ENDOSCOPISTS
VL Thambawita, I Strümke, S Hicks, MA Riegler, P Halvorsen, S Parasa
Gastrointestinal Endoscopy 93 (6), AB190, 2021
22021
Shapley value confidence intervals for attributing variance explained
D Fryer, I Strümke, H Nguyen
Frontiers in Applied Mathematics and Statistics, 58, 2020
22020
Artificial intelligence in dry eye disease
AM Storås, I Strümke, MA Riegler, J Grauslund, HL Hammer, A Yazidi, ...
The ocular surface 23, 74-86, 2022
12022
The social dilemma in artificial intelligence development and why we have to solve it
I Strümke, M Slavkovik, VI Madai
AI and Ethics, 1-11, 2021
12021
Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images
V Thambawita, I Strümke, SA Hicks, P Halvorsen, S Parasa, MA Riegler
Diagnostics 11 (12), 2183, 2021
12021
DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine
V Thambawita, JL Isaksen, SA Hicks, J Ghouse, G Ahlberg, A Linneberg, ...
Scientific reports 11 (1), 1-8, 2021
12021
Explaining a Deep Reinforcement Learning Docking Agent Using Linear Model Trees with User Adapted Visualization
VB Gjærum, I Strümke, OA Alsos, AM Lekkas
Journal of Marine Science and Engineering 9 (11), 1178, 2021
12021
Artificial Intelligence in Medicine: Gastroenterology
I Strümke, SA Hicks, V Thambawita, D Jha, S Parasa, MA Riegler, ...
Artificial Intelligence in Medicine, 1-20, 2021
12021
Model independent feature attributions: Shapley values that uncover non-linear dependencies
DV Fryer, I Strumke, N Hien
PeerJ Computer Science 7 (e582), 2021
12021
Fr615 impact of image resolution on convolutional neural networks performance in gastrointestinal endoscopy
VL Thambawita, S Hicks, I Strümke, MA Riegler, P Halvorsen, S Parasa
Gastroenterology 160 (6), S-377, 2021
12021
DeepFake electrocardiograms: the key for open science for artificial intelligence in medicine
VL Thambawita, JL Isaksen, S Hicks, J Ghouse, G Ahlberg, A Linneberg, ...
medRxiv, 2021
12021
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Articles 1–20