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PloS one, 2019, Volume 14, Issue 6, p. e0218713
In recent months, multiple publications have demonstrated the use of convolutional neural networks (CNN) to classify images of skin cancer as precisely as... 
Journal Article
PEERJ, ISSN 2167-8359, 04/2019, Volume 7, p. e6335
Recent years have seen a growing awareness of the role the immune system plays in successful cancer treatment, especially in novel therapies like... 
Deep learning | DENSITY | Lung cancer | MULTIDISCIPLINARY SCIENCES | VALIDATION | CLASSIFICATION | Immune cells | Cancer micro-environment | Biomarker quantification | TUMOR MICROENVIRONMENT | Neural networks | Immunotherapy | Medical research | Automation | Breast cancer | Metastasis | Cancer therapies | Pathology | Teaching methods | Algorithms | Biomarkers | Lymphomas | Tumors | Immune system
Journal Article
Oncotarget, ISSN 1949-2553, 04/2019, Volume 10, Issue 26, p. 2515
Since the advent of cetuximab, clinical cancer treatment has evolved from the standard, relatively nonspecific chemo- and radiotherapy with significant... 
Journal Article
JAMA Dermatology, ISSN 2168-6068, 09/2018, Volume 154, Issue 9, pp. 1085 - 1086
This survey study explores whether a single exposure of adult patients in a waiting room to an app that approximates facial UV damage may lead to altered UV... 
DERMATOLOGY | Online First | Research | Letters | Research Letter
Journal Article
European Journal of Cancer, ISSN 0959-8049, 04/2019, Volume 111, pp. 30 - 37
Several recent publications have demonstrated the use of convolutional neural networks to classify images of melanoma at par with board-certified... 
Deep learning | Benchmark | Artificial intelligence | Melanoma | DIAGNOSIS | DERMOSCOPY | ONCOLOGY | SKIN-CANCER | Algorithms | Sensitivity analysis | Dermatology | Artificial neural networks | Benchmarks | Sensitivity | Biopsy | Neural networks | Questionnaires | Classification | Skin | Diagnostic systems | Image classification
Journal Article
European Journal of Cancer, ISSN 0959-8049, 09/2019, Volume 118, pp. 91 - 96
The diagnosis of most cancers is made by a board-certified pathologist based on a tissue biopsy under the microscope. Recent research reveals a high... 
Deep learning | Pathology | Histopathology | Artificial intelligence | Melanoma | DIAGNOSIS | ONCOLOGY | DIGITAL PATHOLOGY | DERMATOLOGISTS | ALGORITHMS | Neural networks | Analysis | Histochemistry | Depth indicators | Artificial neural networks | Nevus | Discordance | Skin cancer | Learning | Accuracy | Sensitivity | Biopsy | Classification | Machine learning | Lesions | Image classification
Journal Article
International Journal of Environmental Research and Public Health, ISSN 1661-7827, 08/2018, Volume 15, Issue 8, p. 1656
Journal Article
by Brinker, Titus J and Hekler, Achim and Enk, Alexander H and Enk, Alexander and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Fröhling, Stefan and Utikal, Jochen Sven and Utikal, Jochen S and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenhöfer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Sondermann, Wiebke and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Gholam, Patrick and Hänßle, Holger and Salzmann, Martin and Schäfer, Sarah and Schäkel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and Stölzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and Bär, Claudia Maria and Bender-Säbelkampf, Sophia and Horbrügger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, Jörg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and Müller, Verena and Thomas, Benjamin and Alamri, Ali Saeed M and ... and Collaborators
European Journal of Cancer, ISSN 0959-8049, 04/2019, Volume 111, pp. 148 - 154
Recent studies have demonstrated the use of convolutional neural networks (CNNs) to classify images of melanoma with accuracies comparable to those achieved by... 
Diagnostics | Artificial intelligence | Melanoma | Skin cancer | DIAGNOSIS | ONCOLOGY | ALGORITHMS | Neural networks | Computer vision | Evaluation | Dermatology | Artificial neural networks | Colleges & universities | Sensitivity | Digital imaging | Classification | Machine learning | Photographs | Image classification
Journal Article
European Journal of Cancer, ISSN 0959-8049, 09/2019, Volume 119, pp. 11 - 17
Melanoma is the most dangerous type of skin cancer but is curable if detected early. Recent publications demonstrated that artificial intelligence is capable... 
Deep learning | Artificial intelligence | Melanoma | Skin cancer | DIAGNOSIS | ONCOLOGY | ALGORITHMS | Skin | Neural networks | Analysis
Journal Article
European Journal of Cancer, ISSN 0959-8049, 09/2019, Volume 119, pp. 30 - 34
Recent research revealed the superiority of artificial intelligence over dermatologists to diagnose melanoma from images. However, 30–50% of all melanomas and... 
Deep learning | Artificial intelligence | Melanoma | Prediction | Skin cancer | DERMOSCOPY | DIAGNOSIS | LESIONS | IMAGE CLASSIFICATION | ONCOLOGY | ABCD RULE | DERMATOLOGISTS | MUTATIONS | SKIN-CANCER | Skin | Algorithms
Journal Article
by Brinker, Titus J and Hekler, Achim and Enk, Alexander H and Enk, Alexander and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Holland-Letz, Tim and Utikal, Jochen Sven and Utikal, Jochen S and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenhöfer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Gholam, Patrick and Hänßle, Holger and Salzmann, Martin and Schäfer, Sarah and Schäkel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and Stölzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and Bär, Claudia Maria and Bender-Säbelkampf, Sophia and Horbrügger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, Jörg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and Müller, Verena and Thomas, Benjamin and Alamri, Ali Saeed M and Baczako, Andrea and ... and Collaborators
European Journal of Cancer, ISSN 0959-8049, 05/2019, Volume 113, pp. 47 - 54
Recent studies have successfully demonstrated the use of deep-learning algorithms for dermatologist-level classification of suspicious lesions by the use of... 
Artificial intelligence | Melanoma | Skin cancer | DIAGNOSIS | ALGORITHMS | ONCOLOGY | Neural networks | Analysis | Medical personnel | Level (quantity) | Dermatology | Physicians | Artificial neural networks | Colleges & universities | Learning | Learning algorithms | Sensitivity | Algorithms | Classification | Machine learning | Lesions | Image classification
Journal Article
Medical Oncology, ISSN 1357-0560, 10/2018, Volume 35, Issue 10, pp. 1 - 9
Journal Article