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Thomas Wolfers
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2020 – today
- 2024
- [j3]Esten H. Leonardsen, Karin Persson, Edvard Grødem, Nicola Dinsdale, Till Schellhorn, James M. Roe, Dídac Vidal-Piñeiro, Øystein Sørensen, Tobias Kaufmann, Eric Westman, Andre F. Marquand, Geir Selbæk, Ole A. Andreassen, Thomas Wolfers, Lars T. Westlye, Yunpeng Wang:
Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence. npj Digit. Medicine 7(1) (2024) - [c2]Hao-Chun Yang, Ole A. Andreassen, Lars Tjelta Westlye, Andre F. Marquand, Christian F. Beckmann, Thomas Wolfers:
Learning Cortical Anomaly through Masked Encoding for Unsupervised Heterogeneity Mapping. ISBI 2024: 1-5 - [i4]Saige Rutherford, Thomas Wolfers, Charlotte J. Fraza, Nathaniel G. Harrnet, Christian F. Beckmann, Henricus G. Ruhe, Andre F. Marquand:
To which reference class do you belong? Measuring racial fairness of reference classes with normative modeling. CoRR abs/2407.19114 (2024) - 2023
- [e4]Ahmed Abdulkadir, Deepti R. Bathula, Nicha C. Dvornek, Sindhuja Tirumalai Govindarajan, Mohamad Habes, Vinod Kumar, Esten H. Leonardsen, Thomas Wolfers, Yiming Xiao:
Machine Learning in Clinical Neuroimaging - 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. Lecture Notes in Computer Science 14312, Springer 2023, ISBN 978-3-031-44857-7 [contents] - [i3]Alexander Frötscher, Jaivardhan Kapoor, Thomas Wolfers, Christian F. Baumgartner:
Unsupervised Anomaly Detection using Aggregated Normative Diffusion. CoRR abs/2312.01904 (2023) - [i2]Hao-Chun Yang, Ole A. Andreassen, Lars Tjelta Westlye, Andre F. Marquand, Christian F. Beckmann, Thomas Wolfers:
Learning Cortical Anomaly through Masked Encoding for Unsupervised Heterogeneity Mapping. CoRR abs/2312.02762 (2023) - 2022
- [j2]Esten H. Leonardsen, Han Peng, Tobias Kaufmann, Ingrid Agartz, Ole A. Andreassen, Elisabeth Gulowsen Celius, Thomas Espeseth, Hanne F. Harbo, Einar A. Høgestøl, Ann-Marie G. de Lange, Andre F. Marquand, Dídac Vidal-Piñeiro, James M. Roe, Geir Selbæk, Øystein Sørensen, Stephen M. Smith, Lars T. Westlye, Thomas Wolfers, Yunpeng Wang:
Deep neural networks learn general and clinically relevant representations of the ageing brain. NeuroImage 256: 119210 (2022) - [j1]Johanna M. M. Bayer, Richard Dinga, Seyed Mostafa Kia, Akhil R. Kottaram, Thomas Wolfers, Jinglei Lv, Andrew Zalesky, Lianne Schmaal, Andre F. Marquand:
Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models. NeuroImage 264: 119699 (2022) - [e3]Ahmed Abdulkadir, Deepti R. Bathula, Nicha C. Dvornek, Mohamad Habes, Seyed Mostafa Kia, Vinod Kumar, Thomas Wolfers:
Machine Learning in Clinical Neuroimaging - 5th International Workshop, MLCN 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. Lecture Notes in Computer Science 13596, Springer 2022, ISBN 978-3-031-17898-6 [contents] - 2021
- [e2]Ahmed Abdulkadir, Seyed Mostafa Kia, Mohamad Habes, Vinod Kumar, Jane Maryam Rondina, Chantal M. W. Tax, Thomas Wolfers:
Machine Learning in Clinical Neuroimaging - 4th International Workshop, MLCN 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings. Lecture Notes in Computer Science 13001, Springer 2021, ISBN 978-3-030-87585-5 [contents] - 2020
- [c1]Seyed Mostafa Kia, Hester Huijsdens, Richard Dinga, Thomas Wolfers, Maarten Mennes, Ole A. Andreassen, Lars T. Westlye, Christian F. Beckmann, Andre F. Marquand:
Hierarchical Bayesian Regression for Multi-site Normative Modeling of Neuroimaging Data. MICCAI (7) 2020: 699-709 - [e1]Seyed Mostafa Kia, Hassan Mohy-ud-Din, Ahmed Abdulkadir, Cher Bass, Mohamad Habes, Jane Maryam Rondina, Chantal M. W. Tax, Hongzhi Wang, Thomas Wolfers, Saima Rathore, Madhura Ingalhalikar:
Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Third International Workshop, MLCN 2020, and Second International Workshop, RNO-AI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings. Lecture Notes in Computer Science 12449, Springer 2020, ISBN 978-3-030-66842-6 [contents] - [i1]Seyed Mostafa Kia, Hester Huijsdens, Richard Dinga, Thomas Wolfers, Maarten Mennes, Ole A. Andreassen, Lars T. Westlye, Christian F. Beckmann, Andre F. Marquand:
Hierarchical Bayesian Regression for Multi-Site Normative Modeling of Neuroimaging Data. CoRR abs/2005.12055 (2020)
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