Published on in Vol 20, No 10 (2018): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11936, first published .
Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

Journals

  1. Triantafyllidis A, Tsanas A. Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature. Journal of Medical Internet Research 2019;21(4):e12286 View
  2. Pacheco A, Krohling R. The impact of patient clinical information on automated skin cancer detection. Computers in Biology and Medicine 2020;116:103545 View
  3. Peine A, Hallawa A, Schöffski O, Dartmann G, Fazlic L, Schmeink A, Marx G, Martin L. A Deep Learning Approach for Managing Medical Consumable Materials in Intensive Care Units via Convolutional Neural Networks: Technical Proof-of-Concept Study. JMIR Medical Informatics 2019;7(4):e14806 View
  4. Hogarty D, Su J, Phan K, Attia M, Hossny M, Nahavandi S, Lenane P, Moloney F, Yazdabadi A. Artificial Intelligence in Dermatology—Where We Are and the Way to the Future: A Review. American Journal of Clinical Dermatology 2020;21(1):41 View
  5. Iglesias-Puzas Á, Boixeda P. Deep learning y DerMATología. Actas Dermo-Sifiliográficas 2020;111(3):192 View
  6. Maron R, Weichenthal M, Utikal J, Hekler A, Berking C, Hauschild A, Enk A, Haferkamp S, Klode J, Schadendorf D, Jansen P, Holland-Letz T, Schilling B, von Kalle C, Fröhling S, Gaiser M, Hartmann D, Gesierich A, Kähler K, Wehkamp U, Karoglan A, Bär C, Brinker T, Schmitt L, Peitsch W, Hoffmann F, Becker J, Drusio C, Jansen P, Klode J, Lodde G, Sammet S, Schadendorf D, Sondermann W, Ugurel S, Zader J, Enk A, Salzmann M, Schäfer S, Schäkel K, Winkler J, Wölbing P, Asper H, Bohne A, Brown V, Burba B, Deffaa S, Dietrich C, Dietrich M, Drerup K, Egberts F, Erkens A, Greven S, Harde V, Jost M, Kaeding M, Kosova K, Lischner S, Maagk M, Messinger A, Metzner M, Motamedi R, Rosenthal A, Seidl U, Stemmermann J, Torz K, Velez J, Haiduk J, Alter M, Bär C, Bergenthal P, Gerlach A, Holtorf C, Karoglan A, Kindermann S, Kraas L, Felcht M, Gaiser M, Klemke C, Kurzen H, Leibing T, Müller V, Reinhard R, Utikal J, Winter F, Berking C, Eicher L, Hartmann D, Heppt M, Kilian K, Krammer S, Lill D, Niesert A, Oppel E, Sattler E, Senner S, Wallmichrath J, Wolff H, Giner T, Glutsch V, Kerstan A, Presser D, Schrüfer P, Schummer P, Stolze I, Weber J, Drexler K, Haferkamp S, Mickler M, Stauner C, Thiem A. Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks. European Journal of Cancer 2019;119:57 View
  7. Thenault R, Kaulanjan K, Darde T, Rioux-Leclercq N, Bensalah K, Mermier M, Khene Z, Peyronnet B, Shariat S, Pradère B, Mathieu R. The Application of Artificial Intelligence in Prostate Cancer Management—What Improvements Can Be Expected? A Systematic Review. Applied Sciences 2020;10(18):6428 View
  8. Singhal A, Shukla R, Kankar P, Dubey S, Singh S, Pachori R. Comparing the capabilities of transfer learning models to detect skin lesion in humans. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 2020;234(10):1083 View
  9. Adegun A, Viriri S. FCN-Based DenseNet Framework for Automated Detection and Classification of Skin Lesions in Dermoscopy Images. IEEE Access 2020;8:150377 View
  10. Zhou Q, Shi Y, Xu Z, Qu R, Xu G. Classifying Melanoma Skin Lesions Using Convolutional Spiking Neural Networks With Unsupervised STDP Learning Rule. IEEE Access 2020;8:101309 View
  11. Hekler A, Utikal J, Enk A, Solass W, Schmitt M, Klode J, Schadendorf D, Sondermann W, Franklin C, Bestvater F, Flaig M, Krahl D, von Kalle C, Fröhling S, Brinker T. Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images. European Journal of Cancer 2019;118:91 View
  12. Han S, Park I, Eun Chang S, Lim W, Kim M, Park G, Chae J, Huh C, Na J. Augmented Intelligence Dermatology: Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders. Journal of Investigative Dermatology 2020;140(9):1753 View
  13. Mont M, Krebs V, Backstein D, Browne J, Mason J, Taunton M, Callaghan J. Artificial Intelligence: Influencing Our Lives in Joint Arthroplasty. The Journal of Arthroplasty 2019;34(10):2199 View
  14. Brinker T, Hekler A, Enk A, Klode J, Hauschild A, Berking C, Schilling B, Haferkamp S, Schadendorf D, Holland-Letz T, Utikal J, von Kalle C, Ludwig-Peitsch W, Sirokay J, Heinzerling L, Albrecht M, Baratella K, Bischof L, Chorti E, Dith A, Drusio C, Giese N, Gratsias E, Griewank K, Hallasch S, Hanhart Z, Herz S, Hohaus K, Jansen P, Jockenhöfer F, Kanaki T, Knispel S, Leonhard K, Martaki A, Matei L, Matull J, Olischewski A, Petri M, Placke J, Raub S, Salva K, Schlott S, Sody E, Steingrube N, Stoffels I, Ugurel S, Zaremba A, Gebhardt C, Booken N, Christolouka M, Buder-Bakhaya K, Bokor-Billmann T, Enk A, Gholam P, Hänßle H, Salzmann M, Schäfer S, Schäkel K, Schank T, Bohne A, Deffaa S, Drerup K, Egberts F, Erkens A, Ewald B, Falkvoll S, Gerdes S, Harde V, Hauschild A, Jost M, Kosova K, Messinger L, Metzner M, Morrison K, Motamedi R, Pinczker A, Rosenthal A, Scheller N, Schwarz T, Stölzl D, Thielking F, Tomaschewski E, Wehkamp U, Weichenthal M, Wiedow O, Bär C, Bender-Säbelkampf S, Horbrügger M, Karoglan A, Kraas L, Faulhaber J, Geraud C, Guo Z, Koch P, Linke M, Maurier N, Müller V, Thomas B, Utikal J, Alamri A, Baczako A, Berking C, Betke M, Haas C, Hartmann D, Heppt M, Kilian K, Krammer S, Lapczynski N, Mastnik S, Nasifoglu S, Ruini C, Sattler E, Schlaak M, Wolff H, Achatz B, Bergbreiter A, Drexler K, Ettinger M, Haferkamp S, Halupczok A, Hegemann M, Dinauer V, Maagk M, Mickler M, Philipp B, Wilm A, Wittmann C, Gesierich A, Glutsch V, Kahlert K, Kerstan A, Schilling B, Schrüfer P. Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal of Cancer 2019;113:47 View
  15. Heidari A, Pham T, Ifegwu I, Burwell R, Armstrong W, Tjoson T, Whyte S, Giorgioni C, Wang B, Wong B, Chen Z. The use of optical coherence tomography and convolutional neural networks to distinguish normal and abnormal oral mucosa. Journal of Biophotonics 2020;13(3) View
  16. Hekler A, Utikal J, Enk A, Hauschild A, Weichenthal M, Maron R, Berking C, Haferkamp S, Klode J, Schadendorf D, Schilling B, Holland-Letz T, Izar B, von Kalle C, Fröhling S, Brinker T, Schmitt L, Peitsch W, Hoffmann F, Becker J, Drusio C, Jansen P, Klode J, Lodde G, Sammet S, Schadendorf D, Sondermann W, Ugurel S, Zader J, Enk A, Salzmann M, Schäfer S, Schäkel K, Winkler J, Wölbing P, Asper H, Bohne A, Brown V, Burba B, Deffaa S, Dietrich C, Dietrich M, Drerup K, Egberts F, Erkens A, Greven S, Harde V, Jost M, Kaeding M, Kosova K, Lischner S, Maagk M, Messinger A, Metzner M, Motamedi R, Rosenthal A, Seidl U, Stemmermann J, Torz K, Velez J, Haiduk J, Alter M, Bär C, Bergenthal P, Gerlach A, Holtorf C, Karoglan A, Kindermann S, Kraas L, Felcht M, Gaiser M, Klemke C, Kurzen H, Leibing T, Müller V, Reinhard R, Utikal J, Winter F, Berking C, Eicher L, Hartmann D, Heppt M, Kilian K, Krammer S, Lill D, Niesert A, Oppel E, Sattler E, Senner S, Wallmichrath J, Wolff H, Gesierich A, Giner T, Glutsch V, Kerstan A, Presser D, Schrüfer P, Schummer P, Stolze I, Weber J, Drexler K, Haferkamp S, Mickler M, Stauner C, Thiem A. Superior skin cancer classification by the combination of human and artificial intelligence. European Journal of Cancer 2019;120:114 View
  17. Brinker T, Hekler A, Enk A, von Kalle C, Huynh D. Enhanced classifier training to improve precision of a convolutional neural network to identify images of skin lesions. PLOS ONE 2019;14(6):e0218713 View
  18. Naeem A, Farooq M, Khelifi A, Abid A. Malignant Melanoma Classification Using Deep Learning: Datasets, Performance Measurements, Challenges and Opportunities. IEEE Access 2020;8:110575 View
  19. Balaji V, Suganthi S, Rajadevi R, Krishna Kumar V, Saravana Balaji B, Pandiyan S. Skin disease detection and segmentation using dynamic graph cut algorithm and classification through Naive Bayes classifier. Measurement 2020;163:107922 View
  20. Keshtkar K, Keshtkar A, Safarpour A. Classifying colorectal cancer or colorectal polyps in endoscopic setting using convolutional neural network: protocol for a systematic review and meta-analysis. F1000Research 2020;9:1086 View
  21. Lopez-Jimenez F, Attia Z, Arruda-Olson A, Carter R, Chareonthaitawee P, Jouni H, Kapa S, Lerman A, Luong C, Medina-Inojosa J, Noseworthy P, Pellikka P, Redfield M, Roger V, Sandhu G, Senecal C, Friedman P. Artificial Intelligence in Cardiology: Present and Future. Mayo Clinic Proceedings 2020;95(5):1015 View
  22. Kadampur M, Al Riyaee S. Skin cancer detection: Applying a deep learning based model driven architecture in the cloud for classifying dermal cell images. Informatics in Medicine Unlocked 2020;18:100282 View
  23. Blum A, Bosch S, Haenssle H, Fink C, Hofmann-Wellenhof R, Zalaudek I, Kittler H, Tschandl P. Künstliche Intelligenz und Smartphone-Programm-Applikationen (Apps). Der Hautarzt 2020;71(9):691 View
  24. Winkler J, Fink C, Toberer F, Enk A, Deinlein T, Hofmann-Wellenhof R, Thomas L, Lallas A, Blum A, Stolz W, Haenssle H. Association Between Surgical Skin Markings in Dermoscopic Images and Diagnostic Performance of a Deep Learning Convolutional Neural Network for Melanoma Recognition. JAMA Dermatology 2019;155(10):1135 View
  25. Hekler A, Utikal J, Enk A, Berking C, Klode J, Schadendorf D, Jansen P, Franklin C, Holland-Letz T, Krahl D, von Kalle C, Fröhling S, Brinker T. Pathologist-level classification of histopathological melanoma images with deep neural networks. European Journal of Cancer 2019;115:79 View
  26. de Carvalho T, Noels E, Wakkee M, Udrea A, Nijsten T. Development of Smartphone Apps for Skin Cancer Risk Assessment: Progress and Promise. JMIR Dermatology 2019;2(1):e13376 View
  27. Brinker T, Schlager G, French L, Jutzi T, Kittler H. Computerassistierte Hautkrebsdiagnose. Der Hautarzt 2020;71(9):669 View
  28. Maron R, Utikal J, Hekler A, Hauschild A, Sattler E, Sondermann W, Haferkamp S, Schilling B, Heppt M, Jansen P, Reinholz M, Franklin C, Schmitt L, Hartmann D, Krieghoff-Henning E, Schmitt M, Weichenthal M, von Kalle C, Fröhling S, Brinker T. Artificial Intelligence and Its Effect on Dermatologists’ Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study. Journal of Medical Internet Research 2020;22(9):e18091 View
  29. Cullell-Dalmau M, Otero-Viñas M, Manzo C. Research Techniques Made Simple: Deep Learning for the Classification of Dermatological Images. Journal of Investigative Dermatology 2020;140(3):507 View
  30. Bajwa M, Muta K, Malik M, Siddiqui S, Braun S, Homey B, Dengel A, Ahmed S. Computer-Aided Diagnosis of Skin Diseases Using Deep Neural Networks. Applied Sciences 2020;10(7):2488 View
  31. Shen J, Zhang C, Jiang B, Chen J, Song J, Liu Z, He Z, Wong S, Fang P, Ming W. Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review. JMIR Medical Informatics 2019;7(3):e10010 View
  32. Canales C, Lee C, Cannesson M. Science Without Conscience Is but the Ruin of the Soul. Anesthesia & Analgesia 2020;130(5):1234 View
  33. Kutzner H, Jutzi T, Krahl D, Krieghoff‐Henning E, Heppt M, Hekler A, Schmitt M, Maron R, Fröhling S, Kalle C, Brinker T. Overdiagnosis of melanoma – causes, consequences and solutions. JDDG: Journal der Deutschen Dermatologischen Gesellschaft 2020;18(11):1236 View
  34. Reiter O, Rotemberg V, Kose K, Halpern A. Artificial Intelligence in Skin Cancer. Current Dermatology Reports 2019;8(3):133 View
  35. Nakamura I. Phase diagrams of polymer-containing liquid mixtures with a theory-embedded neural network. New Journal of Physics 2020;22(1):015001 View
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  38. Yu K, Syed M, Bernardis E, Gelfand J. Machine Learning Applications in the Evaluation and Management of Psoriasis: A Systematic Review. Journal of Psoriasis and Psoriatic Arthritis 2020;5(4):147 View
  39. Iglesias-Puzas Á, Boixeda P. Deep Learning and Mathematical Models in Dermatology. Actas Dermo-Sifiliográficas (English Edition) 2020;111(3):192 View
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Books/Policy Documents

  1. Singh N, Kaur A. Interdisciplinary Approaches to Altering Neurodevelopmental Disorders. View
  2. Martorell-Marugán J, Tabik S, Benhammou Y, del Val C, Zwir I, Herrera F, Carmona-Sáez P. Computational Biology. View
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  7. Janoria H, Minj J, Patre P. Intelligent Data Communication Technologies and Internet of Things. View
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  9. Dwivedi P, Sandhu S, Zeeshan M, Sarkar P. Soft Computing Techniques and Applications. View
  10. Mehra A, Bhati A, Kumar A, Malhotra R. Emerging Technologies in Data Mining and Information Security. View
  11. Dutta A, Kamrul Hasan M, Ahmad M. Proceedings of International Joint Conference on Advances in Computational Intelligence. View
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  13. Das T, Kumar V, Prakash A, Lynn A. Skin Cancer: Pathogenesis and Diagnosis. View
  14. Nunnari F, Kadir M, Sonntag D. Machine Learning and Knowledge Extraction. View