A systematic review of olfactory related questionnaires and scales

Han, P., Su, T., Qin, M., Chen, H. & Hummel, T., 1 Apr 2021, In: Rhinology. 59, 2, p. 133-143 11 p.

Research output: Contribution to journal › Review article › Contributed › peer-review

Neural connectome prospectively encodes the risk of post-traumatic stress disorder (PTSD) symptom during the COVID-19 pandemic

Chen, Z., Feng, P., Becker, B., Xu, T., Nassar, M. R., Sirois, F., Hommel, B., & 7 othersZhang, C., He, Q., Qiu, J., He, L., Lei, X., Chen, H. & Feng, T., Nov 2021, In: Neurobiology of stress. 15, 10 p., 100378.

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Extracting structured information from unstructured histopathology reports using generative pre-trained transformer 4 (GPT-4)

Truhn, D., Loeffler, C. M. L., Müller-Franzes, G., Nebelung, S., Hewitt, K. J., Brandner, S., Bressem, K. K., & 2 othersFoersch, S. & Kather, J. N., 2023, In: Journal of pathology. 262, 3, 10 p.

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Novel biomarker SARIFA in colorectal cancer: highly prognostic, not genetically driven and histologic indicator of a distinct tumor biology

Reitsam, N. G., Grozdanov, V., Löffler, C. M. L., Muti, H. S., Grosser, B., Kather, J. N. & Märkl, B., Feb 2024, In: Cancer Gene Therapy. 31 (2024), 2, p. 207-216 10 p.

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Direct prediction of genetic aberrations from pathology images in gastric cancer with swarm learning

Saldanha, O. L., Muti, H. S., Grabsch, H. I., Langer, R., Dislich, B., Kohlruss, M., Keller, G., & 8 othersvan Treeck, M., Hewitt, K. J., Kolbinger, F. R., Veldhuizen, G. P., Boor, P., Foersch, S., Truhn, D. & Kather, J. N., 20 Oct 2022, In: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 26 (2023), 2, p. 264-274 11 p.

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Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study

Niehues, J. M., Quirke, P., West, N. P., Grabsch, H. I., van Treeck, M., Schirris, Y., Veldhuizen, G. P., & 12 othersHutchins, G. G. A., Richman, S. D., Foersch, S., Brinker, T. J., Fukuoka, J., Bychkov, A., Uegami, W., Truhn, D., Brenner, H., Brobeil, A., Hoffmeister, M. & Kather, J. N., 18 Apr 2023, In: Cell Reports : Medicine. 4, 4, 100980.

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Deep learning for dual detection of microsatellite instability and POLE mutations in colorectal cancer histopathology

Gustav, M., Reitsam, N. G., Carrero, Z. I., Loeffler, C. M. L., van Treeck, M., Yuan, T., West, N. P., & 11 othersQuirke, P., Brinker, T. J., Brenner, H., Favre, L., Märkl, B., Stenzinger, A., Brobeil, A., Hoffmeister, M., Calderaro, J., Pujals, A. & Kather, J. N., 23 May 2024, In: npj Precision Oncology. 8 (2024), 1, 11 p., 115.

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Automated curation of large-scale cancer histopathology image datasets using deep learning

Hilgers, L., Ghaffari Laleh, N., West, N. P., Westwood, A., Hewitt, K. J., Quirke, P., Grabsch, H. I., & 9 othersCarrero, Z. I., Matthaei, E., Loeffler, C. M. L., Brinker, T. J., Yuan, T., Brenner, H., Brobeil, A., Hoffmeister, M. & Kather, J. N., Jun 2024, In: Histopathology. 84 (2024), 7, p. 1139-1153 15 p.

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Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance

Niehues, J. M., Müller-Franzes, G., Schirris, Y., Wagner, S. J., Jendrusch, M., Kloor, M., Pearson, A. T., & 6 othersMuti, H. S., Hewitt, K. J., Veldhuizen, G. P., Zigutyte, L., Truhn, D. & Kather, J. N., Jun 2024, In: Computers in biology and medicine. 175 (2024), 12 p., 108410.

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Regression-based Deep-Learning predicts molecular biomarkers from pathology slides

El Nahhas, O. S. M., Loeffler, C. M. L., Carrero, Z. I., van Treeck, M., Kolbinger, F. R., Hewitt, K. J., Muti, H. S., & 10 othersGraziani, M., Zeng, Q., Calderaro, J., Ortiz-Brüchle, N., Yuan, T., Hoffmeister, M., Brenner, H., Brobeil, A., Reis-Filho, J. S. & Kather, J. N., 10 Feb 2024, In: Nature communications. 15 (2024), 1, 13 p., 1253.

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