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Deep learning to predict breast cancer sentinel lymph node status on INSEMA histological images.
Marmé F, Krieghoff-Henning E, Gerber B, Schmitt M, Zahm DM, Bauerschlag D, Forstbauer H, Hildebrandt G, Ataseven B, Brodkorb T, Denkert C, Stachs A, Krug D, Heil J, Golatta M, Kühn T, Nekljudova V, Gaiser T, Schönmehl R, Brochhausen C, Loibl S, Reimer T, Brinker TJ. Marmé F, et al. Among authors: schmitt m. Eur J Cancer. 2023 Dec;195:113390. doi: 10.1016/j.ejca.2023.113390. Epub 2023 Oct 18. Eur J Cancer. 2023. PMID: 37890350 Free article.
Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours.
Brinker TJ, Kiehl L, Schmitt M, Jutzi TB, Krieghoff-Henning EI, Krahl D, Kutzner H, Gholam P, Haferkamp S, Klode J, Schadendorf D, Hekler A, Fröhling S, Kather JN, Haggenmüller S, von Kalle C, Heppt M, Hilke F, Ghoreschi K, Tiemann M, Wehkamp U, Hauschild A, Weichenthal M, Utikal JS. Brinker TJ, et al. Among authors: schmitt m. Eur J Cancer. 2021 Sep;154:227-234. doi: 10.1016/j.ejca.2021.05.026. Epub 2021 Jul 20. Eur J Cancer. 2021. PMID: 34298373 Free article.
Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer.
Wessels F, Schmitt M, Krieghoff-Henning E, Jutzi T, Worst TS, Waldbillig F, Neuberger M, Maron RC, Steeg M, Gaiser T, Hekler A, Utikal JS, von Kalle C, Fröhling S, Michel MS, Nuhn P, Brinker TJ. Wessels F, et al. Among authors: schmitt m. BJU Int. 2021 Sep;128(3):352-360. doi: 10.1111/bju.15386. Epub 2021 May 5. BJU Int. 2021. PMID: 33706408
Reply to the letter to the editor: 'Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images'.
Hekler A, Utikal JS, Solass W, Schmitt M, Klode J, Schadendorf D, Sondermann W, Franklin C, Bestvater F, Krahl D, von Kalle C, Fröhling S, Brinker TJ. Hekler A, et al. Among authors: schmitt m. Eur J Cancer. 2020 May;130:262-264. doi: 10.1016/j.ejca.2019.12.024. Epub 2020 Jan 30. Eur J Cancer. 2020. PMID: 32008919 Free article. No abstract available.
Deep learning can predict survival directly from histology in clear cell renal cell carcinoma.
Wessels F, Schmitt M, Krieghoff-Henning E, Kather JN, Nientiedt M, Kriegmair MC, Worst TS, Neuberger M, Steeg M, Popovic ZV, Gaiser T, von Kalle C, Utikal JS, Fröhling S, Michel MS, Nuhn P, Brinker TJ. Wessels F, et al. Among authors: schmitt m. PLoS One. 2022 Aug 17;17(8):e0272656. doi: 10.1371/journal.pone.0272656. eCollection 2022. PLoS One. 2022. PMID: 35976907 Free PMC article.
A self-supervised vision transformer to predict survival from histopathology in renal cell carcinoma.
Wessels F, Schmitt M, Krieghoff-Henning E, Nientiedt M, Waldbillig F, Neuberger M, Kriegmair MC, Kowalewski KF, Worst TS, Steeg M, Popovic ZV, Gaiser T, von Kalle C, Utikal JS, Fröhling S, Michel MS, Nuhn P, Brinker TJ. Wessels F, et al. Among authors: schmitt m. World J Urol. 2023 Aug;41(8):2233-2241. doi: 10.1007/s00345-023-04489-7. Epub 2023 Jun 29. World J Urol. 2023. PMID: 37382622 Free PMC article.
Artificial intelligence to predict oncological outcome directly from hematoxylin and eosin-stained slides in urology.
Wessels F, Kuntz S, Krieghoff-Henning E, Schmitt M, Braun V, Worst TS, Neuberger M, Steeg M, Gaiser T, Fröhling S, Michel MS, Nuhn P, Brinker TJ. Wessels F, et al. Among authors: schmitt m. Minerva Urol Nephrol. 2022 Oct;74(5):538-550. doi: 10.23736/S2724-6051.22.04758-9. Epub 2022 Mar 11. Minerva Urol Nephrol. 2022. PMID: 35274903 Free article. Review.
Hidden Variables in Deep Learning Digital Pathology and Their Potential to Cause Batch Effects: Prediction Model Study.
Schmitt M, Maron RC, Hekler A, Stenzinger A, Hauschild A, Weichenthal M, Tiemann M, Krahl D, Kutzner H, Utikal JS, Haferkamp S, Kather JN, Klauschen F, Krieghoff-Henning E, Fröhling S, von Kalle C, Brinker TJ. Schmitt M, et al. J Med Internet Res. 2021 Feb 2;23(2):e23436. doi: 10.2196/23436. J Med Internet Res. 2021. PMID: 33528370 Free PMC article.
2,982 results