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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: von kalle c. PLoS One. 2022 Aug 17;17(8):e0272656. doi: 10.1371/journal.pone.0272656. eCollection 2022. PLoS One. 2022. PMID: 35976907 Free PMC article.
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. Among authors: von kalle c. J Med Internet Res. 2021 Feb 2;23(2):e23436. doi: 10.2196/23436. J Med Internet Res. 2021. PMID: 33528370 Free PMC 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: von kalle c. BJU Int. 2021 Sep;128(3):352-360. doi: 10.1111/bju.15386. Epub 2021 May 5. BJU Int. 2021. PMID: 33706408
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: von kalle c. 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 can predict lymph node status directly from histology in colorectal cancer.
Kiehl L, Kuntz S, Höhn J, Jutzi T, Krieghoff-Henning E, Kather JN, Holland-Letz T, Kopp-Schneider A, Chang-Claude J, Brobeil A, von Kalle C, Fröhling S, Alwers E, Brenner H, Hoffmeister M, Brinker TJ. Kiehl L, et al. Among authors: von kalle c. Eur J Cancer. 2021 Nov;157:464-473. doi: 10.1016/j.ejca.2021.08.039. Epub 2021 Oct 11. Eur J Cancer. 2021. PMID: 34649117 Free article.
Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study.
Maron RC, Utikal JS, Hekler A, Hauschild A, Sattler E, Sondermann W, Haferkamp S, Schilling B, Heppt MV, Jansen P, Reinholz M, Franklin C, Schmitt L, Hartmann D, Krieghoff-Henning E, Schmitt M, Weichenthal M, von Kalle C, Fröhling S, Brinker TJ. Maron RC, et al. Among authors: von kalle c. J Med Internet Res. 2020 Sep 11;22(9):e18091. doi: 10.2196/18091. J Med Internet Res. 2020. PMID: 32915161 Free PMC article.
Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark.
Brinker TJ, Hekler A, Hauschild A, Berking C, Schilling B, Enk AH, Haferkamp S, Karoglan A, von Kalle C, Weichenthal M, Sattler E, Schadendorf D, Gaiser MR, Klode J, Utikal JS. Brinker TJ, et al. Among authors: von kalle c. Eur J Cancer. 2019 Apr;111:30-37. doi: 10.1016/j.ejca.2018.12.016. Epub 2019 Feb 22. Eur J Cancer. 2019. PMID: 30802784 Free article.
343 results