Publications
2022
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. Deep learning can predict survival directly from histology in clear cell renal cell carcinoma. PLoS One. 2022 Aug 17;17(8):e0272656. doi: 10.1371/journal.pone.0272656. PMID: 35976907; PMCID: PMC9385058.
Maron RC, Hekler A, Haggenmüller S, von Kalle C, Utikal JS, Müller V, Gaiser M, Meier F, Hobelsberger S, Gellrich FF, Sergon M, Hauschild A, French LE, Heinzerling L, Schlager JG, Ghoreschi K, Schlaak M, Hilke FJ, Poch G, Korsing S, Berking C, Heppt MV, Erdmann M, Haferkamp S, Schadendorf D, Sondermann W, Goebeler M, Schilling B, Kather JN, Fröhling S, Lipka DB, Krieghoff-Henning E, Brinker TJ. Model soups improve performance of dermoscopic skin cancer classifiers. Eur J Cancer. 2022 Sep;173:307-316. doi: 10.1016/j.ejca.2022.07.002. Epub 2022 Aug 13. PMID: 35973360.
Kurz A, Hauser K, Mehrtens HA, Krieghoff-Henning E, Hekler A, Kather JN, Fröhling S, von Kalle C, Brinker TJ. Uncertainty Estimation in Medical Image Classification: Systematic Review. JMIR Med Inform. 2022 Aug 2;10(8):e36427. doi: 10.2196/36427. PMID: 35916701; PMCID: PMC9382553.
Schneider L, Krieghoff-Henning E, Laiouar-Pedari S, Kuntz S, Hekler A, Kather JN, Gaiser T, Fröhling S, Brinker TJ. Response to letter entitled: Re: Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review. Eur J Cancer. 2022 Sep;172:403-404. doi: 10.1016/j.ejca.2022.06.001. Epub 2022 Jun 30. PMID: 35781181.
Ghaffari Laleh N, Muti HS, Loeffler CML, Echle A, Saldanha OL, Mahmood F, Lu MY, Trautwein C, Langer R, Dislich B, Buelow RD, Grabsch HI, Brenner H, Chang-Claude J, Alwers E, Brinker TJ, Khader F, Truhn D, Gaisa NT, Boor P, Hoffmeister M, Schulz V, Kather JN. Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Med Image Anal. 2022 Jul;79:102474. doi: 10.1016/j.media.2022.102474. Epub 2022 May 4. PMID: 35588568.
Saldanha OL, Quirke P, West NP, James JA, Loughrey MB, Grabsch HI, Salto-Tellez M, Alwers E, Cifci D, Ghaffari Laleh N, Seibel T, Gray R, Hutchins GGA, Brenner H, van Treeck M, Yuan T, Brinker TJ, Chang-Claude J, Khader F, Schuppert A, Luedde T, Trautwein C, Muti HS, Foersch S, Hoffmeister M, Truhn D, Kather JN. Swarm learning for decentralized artificial intelligence in cancer histopathology. Nat Med. 2022 Jun;28(6):1232-1239. doi: 10.1038/s41591-022-01768-5. Epub 2022 Apr 25. PMID: 35469069; PMCID: PMC9205774.
Hauser K, Kurz A, Haggenmüller S, Maron RC, von Kalle C, Utikal JS, Meier F, Hobelsberger S, Gellrich FF, Sergon M, Hauschild A, French LE, Heinzerling L, Schlager JG, Ghoreschi K, Schlaak M, Hilke FJ, Poch G, Kutzner H, Berking C, Heppt MV, Erdmann M, Haferkamp S, Schadendorf D, Sondermann W, Goebeler M, Schilling B, Kather JN, Fröhling S, Lipka DB, Hekler A, Krieghoff-Henning E, Brinker TJ. Explainable artificial intelligence in skin cancer recognition: A systematic review. Eur J Cancer. 2022 Apr 4;167:54-69. doi: 10.1016/j.ejca.2022.02.025.
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. Artificial intelligence to predict oncological outcome directly from hematoxylin & eosin-stained slides in urology: a systematic review. Minerva Urol Nephrol. 2022 Mar 11. doi: 10.23736/S2724-6051.22.04758-9.
Echle A, Ghaffari Laleh N, Quirke P, Grabsch HI, Muti HS, Saldanha OL, Brockmoeller SF, van den Brandt PA, Hutchins GGA, Richman SD, Horisberger K, Galata C, Ebert MP, Eckardt M, Boutros M, Horst D, Reissfelder C, Alwers E, Brinker TJ, Langer R, Jenniskens JCA, Offermans K, Mueller W, Gray R, Gruber SB, Greenson JK, Rennert G, Bonner JD, Schmolze D, Chang-Claude J, Brenner H, Trautwein C, Boor P, Jaeger D, Gaisa NT, Hoffmeister M, West NP, Kather JN. Artificial intelligence for detection of microsatellite instability in colorectal cancer-a multicentric analysis of a pre-screening tool for clinical application. ESMO Open. 2022 Mar 2;7(2):100400. doi: 10.1016/j.esmoop.2022.100400.
2021
Schneider L, Laiouar-Pedari S, Kuntz S, Krieghoff-Henning E, Hekler A, Kather JN, Gaiser T, Fröhling S, Brinker TJ. Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review. Eur J Cancer. 2022 Jan;160:80-91.
Haggenmüller S, Maron RC, Hekler A, Utikal JS, Barata C, Barnhill RL, Beltraminelli H, Berking C, Betz-Stablein B, Blum A, Braun SA, Carr R, Combalia M, Fernandez-Figueras MT, Ferrara G, Fraitag S, French LE, Gellrich FF, Ghoreschi K, Goebeler M, Guitera P, Haenssle HA, Haferkamp S, Heinzerling L, Heppt MV, Hilke FJ, Hobelsberger S, Krahl D, Kutzner H, Lallas A, Liopyris K, Llamas-Velasco M, Malvehy J, Meier F, Müller CSL, Navarini AA, Navarrete-Dechent C, Perasole A, Poch G, Podlipnik S, Requena L, Rotemberg VM, Saggini A, Sangueza OP, Santonja C, Schadendorf D, Schilling B, Schlaak M, Schlager JG, Sergon M, Sondermann W, Soyer HP, Starz H, Stolz W, Vale E, Weyers W, Zink A, Krieghoff-Henning E, Kather JN, von Kalle C, Lipka DB, Fröhling S, Hauschild A, Kittler H, Brinker TJ. Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts. Eur J Cancer. 2021 Oct;156:202-216. doi: 10.1016/j.ejca.2021.06.049.
Maron RC, Schlager JG, Haggenmüller S, von Kalle C, Utikal JS, Meier F, Gellrich FF, Hobelsberger S, Hauschild A, French L, Heinzerling L, Schlaak M, Ghoreschi K, Hilke FJ, Poch G, Heppt MV, Berking C, Haferkamp S, Sondermann W, Schadendorf D, Schilling B, Goebeler M, Krieghoff-Henning E, Hekler A, Fröhling S, Lipka DB, Kather JN, Brinker TJ. A benchmark for neural network robustness in skin cancer classification. Eur J Cancer. 2021 Sep;155:191-199. doi: 10.1016/j.ejca.2021.06.047. Epub 2021 Aug 11.
Brockmoeller S, Echle A, Ghaffari Laleh N, Eiholm S, Malmstrøm ML, Plato Kuhlmann T, Levic K, Grabsch HI, West NP, Saldanha OL, Kouvidi K, Bono A, Heij LR, Brinker TJ, Gögenür I, Quirke P, Kather JN. Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer. J Pathol. 2022 Mar;256(3):269-281.
Steeb T, Wessely A, Petzold A, Brinker TJ, Schmitz L, Leiter U, Garbe C, Schöffski O, Berking C, Heppt MV. Evaluation of Long-term Clearance Rates of Interventions for Actinic Keratosis: A Systematic Review and Network Meta-analysis. JAMA Dermatol. 2021 Sep 1;157(9):1066-1077. doi: 10.1001/jamadermatol.2021.2779. PMID: 34347015; PMCID: PMC8340012.
Schrammen PL, Ghaffari Laleh N, Echle A, Truhn D, Schulz V, Brinker TJ, Brenner H, Chang-Claude J, Alwers E, Brobeil A, Kloor M, Heij LR, Jäger D, Trautwein C, Grabsch HI, Quirke P, West NP, Hoffmeister M, Kather JN. Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology. J Pathol. 2022 Jan;256(1):50-60.
Loeffler CML, Ortiz Bruechle N, Jung M, Seillier L, Rose M, Laleh NG, Knuechel R, Brinker TJ, Trautwein C, Gaisa NT, Kather JN. Artificial Intelligence-based Detection of FGFR3 Mutational Status Directly from Routine Histology in Bladder Cancer: A Possible Preselection for Molecular Testing? Eur Urol Focus. 2021 Apr 21:S2405-4569(21)00113-9.
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. Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours. Eur J Cancer. 2021 Sep;154:227-234.
Steeb T, Wessely A, Petzold A, Brinker TJ, Schmitz L, Schöffski O, Berking C, Heppt MV. Long-term recurrence rates of actinic keratosis: A systematic review and pooled analysis of randomized controlled trials. J Am Acad Dermatol. 2021 Apr 16:S0190-9622(21)00815-X.
Bernardes-Souza B, Júnior SRC, Santos CA, Neto RMDN, Bottega FC, Godoy DC, Freitas BL, Silva DLG, Brinker TJ, Nascimento RA, Tupinambás U, Reis AB, Coura-Vital W. Logistics Workers Are a Key Factor for SARS-CoV-2 Spread in Brazilian Small Towns: Case-Control Study. JMIR Public Health Surveill. 2021 Sep 1;7(9):e30406.
Kuntz S, Krieghoff-Henning E, Kather JN, Jutzi T, Höhn J, Kiehl L, Hekler A, Alwers E, von Kalle C, Fröhling S, Utikal JS, Brenner H, Hoffmeister M, Brinker TJ. Gastrointestinal cancer classification and prognostication from histology using deep learning: Systematic review. Eur J Cancer. 2021
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. Deep learning can predict lymph node status directly from histology in colorectal cancer. Eur J Cancer. 2021 Nov;157:464-473. doi: 10.1016/j.ejca.2021.08.039. Epub 2021 Oct 11.
Höhn J, Krieghoff-Henning E, Jutzi TB, von Kalle C, Utikal JS, Meier F, Gellrich FF, Hobelsberger S, Hauschild A, Schlager JG, French L, Heinzerling L, Schlaak M, Ghoreschi K, Hilke FJ, Poch G, Kutzner H, Heppt MV, Haferkamp S, Sondermann W, Schadendorf D, Schilling B, Goebeler M, Hekler A, Fröhling S, Lipka DB, Kather JN, Krahl D, Ferrara G, Haggenmüller S, Brinker TJ.* Combining CNN-based histologic whole slide image analysis and patient data to improve skin cancer classification. European Journal of Cancer. 2021 May 1;149:94–101.
Haggenmüller S, Krieghoff-Henning E, Jutzi T, Trapp N, Kiehl L, Utikal JS, Fabian S, Brinker TJ. Digital Natives' Preferences on Mobile Artificial Intelligence Apps for Skin Cancer Diagnostics: Survey Study. JMIR Mhealth Uhealth. 2021 Aug 27;9(8):e22909.
Höhn, J., Hekler, A., Krieghoff-Henning, E., Kather, J. N., Utikal, J. S., Meier, F., ... & Brinker, T. J. (2021). Integrating patient data into skin cancer classification using convolutional neural networks: systematic review. Journal of Medical Internet Research, 23(7), e20708.
Maron R.C., Hekler A., Krieghoff-Henning E., Schmitt M., Schlager J.G., Utikal J.S., Brinker T.J.* Reducing the Impact of Confounding Factors on Skin Cancer Classification via Image Segmentation: Technical Model Study. J Med Internet Res. 2021 Mar 25;23(3): e21695.
Wessels F., Schmitt M., Krieghoff-Henning E., Jutzi T., Worst T.S., Waldbillig F., Neuberger M., Maron R.C., Steeg M., Gaiser T., Hekler A., Utikal J.S., von Kalle C., Fröhling S., Michel M.S., Nuhn P., Brinker T.J.* Deep learning approach to predict lymph node metastasis directly from primary tumor histology in prostate cancer. BJU Int. 2021 Mar 11.
Brinker T.J.*, Schmitt M., Krieghoff-Henning E.I., Barnhill R., Beltraminelli H., Braun S.A., Carr R., Fernandez-Figueras M.T., Ferrara G., Fraitag S., Gianotti R., Llamas-Velasco M., Müller C.S.L., Perasole A., Requena L., Sangueza O.P., Santonja C., Starz H., Vale E., Weyers W., Hekler A., Kather J.N., Fröhling S., Krahl D., Holland-Letz T., Utikal J.S., Saggini A., Kutzner H. Diagnostic performance of artificial intelligence for histologic melanoma recognition compared to 18 international expert pathologists. J Am Acad Dermatol. 2021 Feb 11:S0190-9622(21)00331-5.
Hornung A., Steeb T., Wessely A., Brinker T.J., Breakell T., Erdmann M., Berking C., Heppt M.V.* The Value of Total Body Photography for the Early Detection of Melanoma: A Systematic Review. Int J Environ Res Public Health. 2021 Feb 10;18(4):1726. Review.
Krause J., Grabsch H.I., Kloor M., Jendrusch M., Echle A., Buelow R.D., Boor P., Luedde T., Brinker T.J., Trautwein C., Pearson A.T., Quirke P., Jenniskens J., Offermans K., van den Brandt P.A., Kather J.N.* Deep learning detects genetic alterations in cancer histology generated by adversarial networks. J Pathol. 2021 Feb 9.
Schmitt M., Maron R.C., Hekler A., Stenzinger A., Hauschild A., Weichenthal M., Tiemann M., Krahl D., Kutzner H., Utikal J.S., Haferkamp S., Kather J.N., Klauschen F., Krieghoff-Henning E., Fröhling S., von Kalle C., Brinker T.J.* Hidden Variables in Deep Learning Digital Pathology and Their Potential to Cause Batch Effects: Prediction Model Study. J Med Internet Res. 2021 Feb 2;23(2)
Maron R.C., Haggenmüller S., von Kalle C., Utikal J.S., Meier F., Gellrich F.F., Hauschild A., French L.E., Schlaak M., Ghoreschi K., Kutzner H., Heppt M.V., Haferkamp S., Sondermann W., Schadendorf D., Schilling B., Hekler A., Krieghoff-Henning E., Kather J.N., Fröhling S., Lipka D.B., Brinker T.J.* Robustness of convolutional neural networks in recognition of pigmented skin lesions. Eur J Cancer. 2021 Mar;145:81-91.
Echle A., Rindtorff N.T., Brinker T.J., Luedde T., Pearson A.T., Kather J.N.* Deep learning in cancer pathology: a new generation of clinical biomarkers. Br J Cancer. 2021 Feb;124(4):686-696. Review.
2020
Jakob L., Steeb T., Fiocco Z., Pumnea T., Jakob S.N., Wessely A., Rothenberger C.C., Brinker T.J., French L.E., Berking C., Heppt M.V.* Patient Perception of Mobile Phone Apps for the Care and Prevention of Sexually Transmitted Diseases: Cross-Sectional Study. JMIR Mhealth Uhealth. 2020 Nov 10;8(11)
Kutzner H., Jutzi T.B., Krahl D., Krieghoff-Henning E.I., Heppt M.V., Hekler A., Schmitt M., Maron R.C.R., Fröhling S., von Kalle C., Brinker T.J.* Überdiagnose von Melanomen - Ursachen, Konsequenzen und Lösungsansätze. J Dtsch Dermatol Ges. 2020 Nov;18(11):1236-1244.
Sondermann W.*, von Kalle C., Utikal J.S., Schadendorf D., Esser S., Durani B., Durani H., Jansen M., Brinker T.J. [External scientific evaluation of the first teledermatology app without direct patient contact in Germany (Online Dermatologist-AppDoc)].
Hautarzt. 2020 Nov;71(11):887-897.
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. Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study. J Med Internet Res. 2020 Sep 11; 22(9):e18091. doi: 10.2196/18091. PMID: 32915161; PMCID: PMC7519424.
Brinker TJ, Schlager G, French LE, Jutzi T, Kittler H. Computerassistierte Hautkrebsdiagnose : Wann kommt künstliche Intelligenz in der Praxis an? [Computer-assisted skin cancer diagnosis : Is it time for artificial intelligence in clinical practice?]. Hautarzt. 2020 Sep; 71(9):669-676. German. doi: 10.1007/s00105-020-04662-8. PMID: 32747996.
Kutzner H, Jutzi TB, Krahl D, Krieghoff-Henning EI, Heppt MV, Hekler A, Schmitt M, Maron RCR, Fröhling S, von Kalle C, Brinker TJ. Overdiagnosis of melanoma - causes, consequences and solutions. J Dtsch Dermatol Ges. 2020 Aug 25. doi: 10.1111/ddg.14233. Epub ahead of print.
Brinker TJ, Faria BL, de Faria OM, Klode J, Schadendorf D, Utikal JS, Mons U, Krieghoff-Henning E, Lisboa OC, Oliveira ACC, Lino HA, Bernardes-Souza B. Effect of a Face-Aging Mobile App-Based Intervention on Skin Cancer Protection Behavior in Secondary Schools in Brazil: A Cluster-Randomized Clinical Trial. JAMA Dermatol. 2020 Jul 1; 156(7):737-745. doi: 10.1001/jamadermatol.2020.0511. PMID: 32374352; PMCID: PMC7203674.
Jutzi TB, Krieghoff-Henning EI, Holland-Letz T, Utikal JS, Hauschild A, Schadendorf D, Sondermann W, Fröhling S, Hekler A, Schmitt M, Maron RC, Brinker TJ. Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective. Front Med (Lausanne). 2020 Jun 2; 7:233. doi: 10.3389/fmed.2020.00233. PMID: 32671078; PMCID: PMC7326111.
Hekler A, Kather JN, Krieghoff-Henning E, Utikal JS, Meier F, Gellrich FF, Upmeier Zu Belzen J, French L, Schlager JG, Ghoreschi K, Wilhelm T, Kutzner H, Berking C, Heppt MV, Haferkamp S, Sondermann W, Schadendorf D, Schilling B, Izar B, Maron R, Schmitt M, Fröhling S, Lipka DB, Brinker TJ. Effects of Label Noise on Deep Learning-Based Skin Cancer Classification. Front Med (Lausanne). 2020 May 6;7:177. doi: 10.3389/fmed.2020.00177. PMID: 32435646; PMCID: PMC7218064.
2019
Sondermann W, Utikal JS, Enk AH, Schadendorf D, Klode J, Hauschild A, Weichenthal M, French LE, Berking C, Schilling B, Haferkamp S, Fröhling S, von Kalle C, Brinker TJ. Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data. Eur J Cancer. 2019 Sep;119:30-34. doi: 10.1016/j.ejca.2019.07.009. Epub 2019 Aug 8. Erratum in: Eur J Cancer. 2019 Dec;123:171. PMID: 31401471.
Hekler A, Utikal JS, Enk AH, Hauschild A, Weichenthal M, Maron RC, Berking C, Haferkamp S, Klode J, Schadendorf D, Schilling B, Holland-Letz T, Izar B, von Kalle C, Fröhling S, Brinker TJ; Collaborators. Superior skin cancer classification by the combination of human and artificial intelligence. Eur J Cancer. 2019 Oct; 120:114-121. doi: 10.1016/j.ejca.2019.07.019. Epub 2019 Sep 10. PMID: 31518967.
Brinker TJ, Hekler A, Enk AH, Berking C, Haferkamp S, Hauschild A, Weichenthal M, Klode J, Schadendorf D, Holland-Letz T, von Kalle C, Fröhling S, Schilling B, Utikal JS. Deep neural networks are superior to dermatologists in melanoma image classification. Eur J Cancer. 2019 Sep; 119:11-17. doi: 10.1016/j.ejca.2019.05.023. Epub 2019 Aug 8. PMID: 31401469.
Maron RC, Weichenthal M, Utikal JS, Hekler A, Berking C, Hauschild A, Enk AH, Haferkamp S, Klode J, Schadendorf D, Jansen P, Holland-Letz T, Schilling B, von Kalle C, Fröhling S, Gaiser MR, Hartmann D, Gesierich A, Kähler KC, Wehkamp U, Karoglan A, Bär C, Brinker TJ; Collabrators. Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks. Eur J Cancer. 2019 Sep;119:57-65. doi: 10.1016/j.ejca.2019.06.013. Epub 2019 Aug 14. PMID: 31419752.
Hekler A, Utikal JS, Enk AH, Solass W, Schmitt M, Klode J, Schadendorf D, Sondermann W, Franklin C, Bestvater F, Flaig MJ, Krahl D, von Kalle C, Fröhling S, Brinker TJ. Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images. Eur J Cancer. 2019 Sep; 118:91-96. doi: 10.1016/j.ejca.2019.06.012. Epub 2019 Jul 18. PMID: 31325876.
Brinker TJ, Hekler A, Enk AH, von Kalle C. Enhanced classifier training to improve precision of a convolutional neural network to identify images of skin lesions. PLoS One. 2019 Jun 24; 14(6):e0218713. doi: 10.1371/journal.pone.0218713. PMID: 31233565; PMCID: PMC6590821.
Hekler A, Utikal JS, Enk AH, Berking C, Klode J, Schadendorf D, Jansen P, Franklin C, Holland-Letz T, Krahl D, von Kalle C, Fröhling S, Brinker TJ. Pathologist-level classification of histopathological melanoma images with deep neural networks. Eur J Cancer. 2019 Jul; 115:79-83. doi: 10.1016/j.ejca.2019.04.021. Epub 2019 May 23. PMID: 31129383.
Brinker TJ, Hekler A, Enk AH, Klode J, Hauschild A, Berking C, Schilling B,Haferkamp S, Schadendorf D, Holland-Letz T, Utikal JS, von Kalle C;Collaborators. Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. Eur J Cancer. 2019 May; 113:47-54. doi: 10.1016/j.ejca.2019.04.001. Epub 2019 Apr 10. PMID: 30981091.
Brinker TJ, Hekler A, Enk AH, Klode J, Hauschild A, Berking C, Schilling B, Haferkamp S, Schadendorf D, Fröhling S, Utikal JS, von Kalle C; Collaborators. A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. Eur J Cancer. 2019 Apr; 111:148-154. doi: 10.1016/j.ejca.2019.02.005. Epub 2019 Mar 8. PMID: 30852421.
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. Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark. Eur J Cancer. 2019 Apr; 111:30-37. doi: 10.1016/j.ejca.2018.12.016. Epub 2019 Feb 22. PMID: 30802784.
2018
Brinker TJ, Hekler A, Utikal JS, Grabe N, Schadendorf D, Klode J, Berking C, Steeb T, Enk AH, von Kalle C. Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review. J Med Internet Res. 2018 Oct 17; 20(10):e11936. doi: 10.2196/11936. PMID: 30333097; PMCID: PMC6231861.