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ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets

K. Schultz, S. Bej, W. Hahn, M. Wolfien, P. Srivastava, and O. Wolkenhauer. Pattern Recognition, (2024)
DOI: https://doi.org/10.1016/j.patcog.2023.110138

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NaviCenta - The disease map for placental researchJ. Scheel, M. Hoch, M. Wolfien, and S. Gupta. Placenta, (November 2023)Artificial Intelligence Reporting Guidelines’ Adherence in Nephrology for Improved Research and Clinical OutcomesA. Salybekov, M. Wolfien, W. Hahn, S. Hidaka, and S. Kobayashi. Biomedicines, (2024)A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic dataN. Ahmadi, Q. Nguyen, M. Sedlmayr, and M. Wolfien. Scientific Reports, 14 (1): 2287 (January 2024)CCR2 macrophage response determines the functional outcome following cardiomyocyte transplantationP. Vasudevan, M. Wolfien, H. Lemcke, C. Lang, A. Skorska, R. Gaebel, A. Galow, D. Koczan, T. Lindner, W. Bergmann and 6 other author(s). Genome Med., 15 (1): 61 (August 2023)Ten topics to get started in medical informatics researchM. Wolfien, N. Ahmadi, K. Fitzer, S. Grummt, K. Heine, I. Jung, D. Krefting, A. Kühn, Y. Peng, I. Reinecke and 7 other author(s). J. Med. Internet Res., (July 2023)Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligenceJ. Eckardt, W. Hahn, C. Röllig, S. Stasik, U. Platzbecker, C. Müller-Tidow, H. Serve, C. Baldus, C. Schliemann, K. Schäfer-Eckart and 9 other author(s). npj Digital Medicine, 7 (1): 76 (March 2024)Streamlining intersectoral provision of real-world health data: a service platform for improved clinical research and patient careK. Hoffmann, I. Nesterow, Y. Peng, E. Henke, D. Barnett, C. Klengel, M. Gruhl, M. Bartos, F. Nüßler, R. Gebler and 7 other author(s). Frontiers in Medicine, (2024)ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasetsK. Schultz, S. Bej, W. Hahn, M. Wolfien, P. Srivastava, and O. Wolkenhauer. Pattern Recognition, (2024)Methods used in the development of common data models for health data: Scoping reviewN. Ahmadi, M. Zoch, P. Kelbert, R. Noll, J. Schaaf, M. Wolfien, and M. Sedlmayr. JMIR Med. Inform., (August 2023)Leptin deficiency-caused behavioral change - A comparative analysis using EthoVision and DeepLabCutD. Bühler, N. Power Guerra, L. Müller, O. Wolkenhauer, M. Düffer, B. Vollmar, A. Kuhla, and M. Wolfien. Front. Neurosci., (March 2023)

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ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets

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ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets