Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images

Hekler, Achim, Utikal, Jochen S., Enk, Alexander H., Solass, Wiebke, Schmitt, Max, Klode, Joachim, Schadendorf, Dirk, Sondermann, Wiebke +7 more·2019·European Journal of Cancer
DOI 10.1016/j.ejca.2019.06.012

Cited by (283)

Items 201–283 of 283

  1. Agentic systems in computational pathology: architectures, evidence, and translational challenges
    Xinyu Lu, Qiankun Li, Yakun Gao, Dong Wei, Mengyao Lyu, Siyuan Ma, Jinyue Li, Yufeng Wu, Linghan Cai, Tianyi Zhang et al. · 2026 · Journal of Translational Medicine
  2. New Opportunities and Challenges for Health Professionals in the era of Artificial Intelligence – Review
    Konrad Warchoł, Adam Jasiura, Marlena Zając, Aleksandra Wójcik, Kamila Giżewska · 2022 · Journal of Education Health and Sport
  3. Recent advances of artificial intelligence in melanoma clinical practice
    Naya, Zijun Lin, Haoyan Shen, Xinguang Liu, Wanrui Ma, Mingfa Wang, Jie Ruan, Hongbin Yu, Sha Ma, Xuerong Sun · 2023 · Melanoma Research
  4. Einsatz künstlicher Intelligenz mittels Deep Learning in der dermatopathologischen Routinediagnostik des Basalzellkarzinoms
    Nicole Duschner, Daniel Otero Baguer, Maximilian Schmidt, Klaus Griewank, Eva N. Hadaschik, Sonja Hetzer, Bettina Wiepjes, Jean Le’Clerc Arrastia, Philipp Jansen, Peter Maaß et al. · 2023 · JDDG Journal der Deutschen Dermatologischen Gesellschaft
  5. Glaucoma Fundus Image Recognition Based on Optimal ROI Proportion and VIT-B/16
    Ge Wang, Hao Peng · 2023 · International Conference on New Trends in Computational Intelligence (NTCI)
  6. Inteligencia artificial en el diagnóstico dermatopatológico
    Mar Llamas‐Velasco, Enrique Ovejero‐Merino · 2024 · Piel
  7. Melanoma cutáneo
    C. Rodríguez López, T. Curiel García, J. Pumares Pérez, M. Mateos González, Vanesa Varela · 2021 · Medicine - Programa de Formación Médica Continuada Acreditado
  8. On modern methods of automated diagnosis of skin tumors in clinical practice
    V. Sergeev, Y. Sergeev, O. Tamrazova, V. Nikitaev, A. N. Pronichev · 2020 · Medical alphabet
  9. Learn and Visually Explain Deep Fair Models: an Application to Face Recognition
    Danilo Franco, Luca Oneto, Nicolò Navarin, Davide Anguita · 2021 · International Joint Conference on Neural Networks (IJCNN)
  10. Artificial intelligence in pathological evaluation of gastrointestinal cancers
    Anıl Alpsoy, Ayşen Yavuz, Gülsüm Özlem Elpek · 2021 · Artificial Intelligence in Gastroenterology
  11. PathoSpotter: Computational Intelligence Applied to Nephropathology
    Luciano Rebouças de Oliveira, Paulo Chagas, Angelo Amâncio Duarte, Rodrigo Tripodi Calumby, Emanuele Santos, Michele Fúlvia Ângelo, Washington dos Santos · 2022 · Springer eBooks
  12. Medical Imaging and Artificial Intelligence
    Luca Casini, Marco Roccetti · 2020 · SpringerBriefs in ethics
  13. Interpretation of smartphone-captured radiographs utilizing a deep learning-based approach
    Hieu X. Le, Phuong Nguyen, Thang H. Nguyen, Khanh N. Q. Le, Nguyen, Thanh T. · 2020 · arXiv (Cornell University)
  14. Artificial Intelligence in Dermatopathology: An Update and Review of the Current Literature
    Abu-Dayeh, Ala’, Cazzato, Gerardo, Giubellino, Alessio · 2026 · Diagnostics
  15. Melanoma Detection Among Various Skin Lesions
    Aurobindo Gupta, Sanjeev Thakur · 2020 · Lecture notes in networks and systems
  16. Real-time intraoperative identification of malignant ovarian tumors using deep learning of clinical gross specimen images
    Chih-Hsuan Sao, I-San Chan, Ying-Chu Shih, Shih-Yao Lin, Yen‐Hou Chang, Albert C. Yang, Yi‐Jen Chen · 2026 · Taiwanese Journal of Obstetrics and Gynecology
  17. Considerations for Specialized Health AI & ML Modelling and Applications: Imaging—Through the Perspective of Dermatology
    Dennis H. Murphree, Anirudh Choudhary, Puneet K. Bhullar, Nneka I. Comfere · 2024 · Health informatics
  18. Large-Scale Dermatopathology Dataset for Lesion Segmentation: Model Development and Analysis
    Yosep Chong, Daseul Park, Youngbin Ahn, Yoonjin Kwak, Seyeon Park, Seung Wan Back, Chang-Woo Lee, Gyeongsin Park, Mohammad Rizwan Alam, B K Kim et al. · 2025 · Journal of Korean Medical Science
  19. Optimization of Convolutional Neural Networks With Multi-Objective Function Metaheuristics for Melanoma Detection
    Pamela Hermosilla, Ricardo Soto, Éric Monfroy, Emanuel Vega, Lucas Erazo, Valentina Guzmán · 2025 · IEEE Access
  20. Bridging traditional and deep learning methods in H&E histological image normalization: a comprehensive review and introducing a novel framework for comparative analyses
    Behnaz Haji Molla Hoseyni, Sevda Imany, Ahmadreza Iranpour, Maryam Mehrabani, Sina Seifouri, Maryam Rafieipour-Jobaneh, Sina Firuzbakht, Ali Masoudi‐Nejad · 2025 · Journal of Advanced Research
  21. AI-Driven Dermatological Cancer Detection: A Vision Transformer Based Novel Approach
    B. Ramasubramanian, A. Sriram, A. Sugantha, S. Priya, A. Shiny Pershiya, M. Vinoth · 2025 · International Conference on Innovative Mechanisms for Industry Applications
  22. Deep learning finds convergent melanocytic morphology despite noisy archival slides
    Mikio Tada, Garrett Gaskins, Sina Ghandian, Nicholas C. Mew, Michael J. Keiser, Elizabeth Keiser · 2025 · Cell Reports Methods
  23. Translating Features to Findings: Deep Learning for Melanoma Subtype Prediction
    Dorra Guermazi, Sarina Khemchandani, Samer Wahood, Cuong V. Nguyen, Elie Saliba · 2025 · Dermatopathology
  24. Applications of Neural Networks in Forensic Medicine
    O. B. Dolgova, Yu. G. Yakimova, P. A. Sayler, Кондрашов Дмитрий Львович, N. R. Shabunina-Basok · 2025 · Ural Medical Journal
  25. Deep Learning-Based Skin Care Detection with Multi-method Explainability: Grad-CAM, Lime, and Occlusion Sensitivity
    Tooba Khan, Muhammad Zeeshan Ul Haque, Gul Munir, Irfan Ahmed Usmani · 2026 · IIUM Engineering Journal
  26. Melan-Dx: a knowledge-enhanced vision-language framework improves differential diagnosis of melanocytic neoplasm pathology
    Jialu Yao, Songhao Li, Peixian Liang, Xiaowei Xu, David E. Elder, Zhi Huang · 2026 · npj Digital Medicine
  27. Überdiagnose von Melanomen – Ursachen, Konsequenzen und Lösungsansätze
    Heinz Kutzner, Tanja B. Jutzi, Dieter Krahl, Eva Krieghoff‐Henning, Markus Vincent Heppt, Achim Hekler, Max Schmitt, Roman C. Maron, Stefan Fröhling, Christof V. Kalle et al. · 2020 · JDDG Journal der Deutschen Dermatologischen Gesellschaft
  28. Hautkrebserkennung: Wie künstliche Intelligenz die Diffenzialdiagnose schärft
    Tanja B. Jutzi, Titus Josef Brinker · 2020 · Deutsches Ärzteblatt
  29. NEURAL NETWORKS FROM KERAS IN SKIN LESION DIAGNOSTIC
    Magdalena Michalska · 2022 · Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska
  30. Artificial Intelligence and Teledermatology
    Kristen Fernandez, Albert T. Young, Abhishek Bhattarcharya, Ayan Kusari, Maria L. Wei · 2023 · Updates in clinical dermatology
  31. Machine Learning in Tissue Polarimetry
    Kausalya Neelavara Makkithaya, Sindhoora Kaniyala Melanthota, Yury V. Kistenev, Alexander V. Bykov, Tatiana Novikova, Igor V. Meglinski, Nirmal Mazumder · 2023 · Biological and medical physics, biomedical engineering
  32. Recognition of Skin Cancer from Dermoscopic Images via DNN
    Liyang Xu, Yiran Chen, Yinglong Wang, Ning Liao, Jiacheng He, Dezheng Wang · 2024 · International Conference on Generative Artificial Intelligence and Information Security (GAIIS)
  33. POSSIBILITIES OF ARTIFICIAL INTELLIGENCE IN ONCOUROLOGY
    Nikolay Karnaukhov, A.V. Maksimenko, M.G. Sogomonyan · 2024 · Современные проблемы науки и образования
  34. Künstliche Intelligenz und maschinelles Lernen in der onkologischen Bildgebung
    Jens Kleesiek, Jacob M. Murray, Christian Strack, Sebastian Prinz, Georgios A. Kaissis, Rickmer Braren · 2020 · Der Pathologe
  35. Artificial Intelligence: Applications in Dermatology
    Dennis H. Murphree, Yong-Hun Kim, Michael Z. Zhang, Anirudh Choudhary, Puneet K. Bhullar, Nneka I. Comfere · 2024 · Springer eBooks
  36. Reply to the letter to the editor: ‘Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images’
    Achim Hekler, Jochen Sven Utikal, Wiebke Solaß, Max Schmitt, Joachim Klode, Dirk Schadendorf, Wiebke Sondermann, Cindy Franklin, Felix Bestvater, Dieter Krahl et al. · 2020 · European Journal of Cancer
  37. Histopathological Image Analysis Using Deep Learning Framework
    SUDHA RANI, Jogendra Kumar Munagala · 2022 · Research Square
  38. Multi-resolution vision transformer model for skin cancer subtype classification using histopathology slides
    Abadh Kishore Chaurasia, Patrick W Toohey, Helen Harris, Alex William Hewitt · 2025 · medRxiv
  39. Quoi de neuf en recherche ?
    Martine Bagot · 2019 · Annales de Dermatologie et de Vénéréologie
  40. Pathological Diagnosis and Analysis of Four Cases of Melanoma in Yunan Black Pigs
    小女 王 · 2020 · Asian Case Reports in Veterinary Medicine
  41. Quoi de neuf en médecine interne ?
    Stéphane Barète · 2019 · Annales de Dermatologie et de Vénéréologie
  42. Artificial Intelligence–Assisted Diagnostic Approaches for Pancreatic Disease
    Jiannis Anastasiou, Emmanuel S. Coronel, Irina Mihaela Cazacu, Adrian Săftoiu, Tyler M. Berzin · 2021 · Pancreas
  43. WITHDRAWN: Artificial intelligence in dermatology: A threat or an opportunity?
    Antonio Martorell, Alejandro Martín-Gorgojo, Elisa Ríos‐Viñuela, J.M. Rueda-Carnero, Fernando Alfageme, R. Taberner · 2021 · Actas Dermo-Sifiliográficas · Retracted
  44. SELECTED APPLICATIONS OF DEEP NEURAL NETWORKS IN SKIN LESION DIAGNOSTIC
    Magdalena Michalska · 2021 · Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska
  45. MULTICLASS SKIN LESS IONS CLASSIFICATION BASED ON DEEP NEURAL NETWORKS
    Magdalena Michalska · 2022 · Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska
  46. Information Technology's Role in Global Healthcare Systems
    Martin Wiesner, Björn Schreiweis · 2022 · MDPI eBooks
  47. GŁĘBOKIE SIECI NEURONOWE DLA DIAGNOSTYKI ZMIAN SKÓRNYCH
    Magdalena Michalska · 2022 · Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska
  48. [Deep learning-based fully automated intelligent and precise diagnosis for melanocytic lesions].
    Tianlei Shi, Jiayi Zhang, Yongyang Bao, Xin Qiang Gao · 2022 · PubMed Central
  49. Artificial intelligence applications in predicting the behavior of gastrointestinal cancers in pathology
    Ayşen Yavuz, Anıl Alpsoy, Elif Ocak Gedik, Mennan Yigitcan Celik, Cumhur İbrahim Başsorgun, Betül Ünal, Gülsüm Özlem Elpek · 2022 · Artificial Intelligence in Gastroenterology
  50. ЦИФРОВА ПАТОЛОГІЯ ПРИ МЕЛАНОМІ: ДОСЯГНЕННЯ, БАР’ЄРИ ТА ПЕРСПЕКТИВИ
    Oleksandr Dudin · 2023 · Medical Informatics and Engineering
  51. Risk Stratification of Malignant Melanoma Using Neural Networks
    Julian Burghoff, Leonhard Ackermann, Younes Salahdine, Veronika Bram, Katharina Wunderlich, Julius Balkenhol, Thomas Dirschka, Hanno Gottschalk · 2023 · Lecture notes in computer science
  52. Grundprinzipien der künstlichen Intelligenz in der Dermatologie erklärt am Beispiel des Melanoms
    Tim Johannes Hartmann, Johannes Passauer, Julien Hartmann, Laura Schmidberger, Manfred Kneilling, Sebastian Volc · 2024 · JDDG Journal der Deutschen Dermatologischen Gesellschaft
  53. Evaluasi tingkat akurasi penggunaan metode deep learning dengan algoritma convolutional neural network pada citra dermatoskopi untuk efisiensi diagnosis kutaneus melanoma: Sebuah telaah literatur sistematis
    Riri Arisanty Syafrin Lubis · 2024 · HOLISTIK JURNAL KESEHATAN
  54. POSSIBILITIES OF APPLYING ARTIFICIAL INTELLIGENCE IN PATHOMORPHOLOGICAL DIAGNOSIS OF SKIN DISEASES
    Nikolay Karnaukhov, К. С. Корчагина, Сынкова Дарья Александровна · 2024 · Современные проблемы науки и образования
  55. In Silico Optimization of Tissue Microarray Design for Machine Learning Analysis
    Addie Woicik, Zachary Ryan McCaw, Santiago Akle, Benjamin Dulken, Sanjana Narayanan, Christopher S. Probert · 2024 · IEEE International Symposium on Biomedical Imaging (ISBI)
  56. Machine-learning convergent melanocytic morphology despite noisy archival slides
    Mikio Tada, Garrett Gaskins, Sina Ghandian, Nicholas C. Mew, Michael J. Keiser, Elizabeth Keiser · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  57. Digital Pathology and Artificial Intelligence for Early Diagnosis of Pediatric Solid Tumors: Implication for Improved Healthcare Strategies
    Negar Shaterian, Mohammadamin Jandaghian-Bidgoli, Negin Shaterian, Sara Salehi, Amirhossein Hajialigol, Parniyan Sadeghi, Noosha Samieefar, Nima Rezaei · 2024 · Interdisciplinary cancer research
  58. PathoSpotter: Angewandte Rechnerintelligenz in der Nephropathologie
    Luciano Rebouças de Oliveira, Paulo Chagas, Angelo Amâncio Duarte, Rodrigo Tripodi Calumby, Emanuele Santos, Michele Fúlvia Ângelo, Washington dos Santos · 2024 · Springer eBooks
  59. Towards Explainable Deep Learning for Non-melanoma Skin Cancer Diagnosis
    A.L. Rooijen van, Karin M. Verspoor, T.B. Kirk, Andy Song · 2024 · Lecture notes in computer science
  60. Use cases in surgical pathology
    Meera Hameed · 2024 · Elsevier eBooks
  61. Melanoma Detection Using Convolutional Neural Network
    Pooja Illangarathne, Nethari Jayasinghe, Sharith Rodrigo, Kanishka Hewageegana, Prasad Wimalaratne · 2025 · International Journal of Machine Learning
  62. Application of deep learning convolutional neural networks to identify gastric squamous cell carcinoma in mice
    Yuke Ren, Shuangxing Li, Di Zhang, Yongtian Zhao, Yanwei Yang, Guitao Huo, Xiaobing Zhou, Xingchao Geng, Zhi Rong Lin, Zhe Qu · 2025 · Frontiers in Medicine
  63. Deep Learning-Based Skin Lesion Classification with Ensemble Stacking and Data Augmentation
    Chia‐Yu Chu, Cheng-Hung Dixson Lin · 2025 · IEEE International Conference on Consumer Technology (ICCT-Pacific)
  64. Extraction of Informative Features for Optical Biopsy Data Analysis
    И. А. Матвеева · 2025 · Systems and Technologies of the Digital HealthCare (STDH)
  65. TEWS: Transformer-empowered weakly supervised prediction of immune score and genetic mutations in liver cancer from whole slide image
    Bin Wang, Xianchuan Chen, Ying Li, Huiqing Wang, Keke Wang, Xiaoyan Li · 2025 · Computational Biology and Chemistry
  66. Artificial Intelligence for Lentigo Maligna: Automated Margin Assessment via Sox-10-Based Melanocyte Density Mapping
    Rieke Löper, Lennart Abels, Daniel Otero Baguer, Felix Bremmer, Michael Peter Schön, Christina Mitteldorf · 2025 · Dermatopathology
  67. Additional file 2 of Validation of machine learning models to detect amyloid pathologies across institutions
    Juan C. Vizcarra, Gearing, Marla, Michael J. Keiser, Glass, Jonathan D., Brittany N. Dugger, Gutman, David A. · 2020 · Figshare
  68. Explainable Skin Cancer Detection via Hybrid CNN and Adaptive Post-hoc Explanations
    Akbar Kushanoor, Sanjay K. Sahay · 2026 · Communications in computer and information science
  69. 265Chapter 12 AI solutions for skin cancer diagnosis and treatment
    Rishabha Malviya, Shivam Rajput, Mukesh Roy, Sathvik Belagodu Sridhar, Sabin Thomas · 2025 · De Gruyter eBooks
  70. Complete tissue sectioning: Combined processing technique for dermatologic studies requiring confirmation of disease clearance
    Marie Clark, Jalal Maghfour, Ben J. Friedman, Jennifer Healy, Molly C. Powers, David Ozog · 2026 · Journal of the American Academy of Dermatology
  71. Radiomics and Artificial Intelligence for personalized treatment of HPV-induced cancers
    Stéphane Niyoteka · 2023
  72. Artificial intelligence in pathology: Perceived diagnostic utility and challenges from a cross-sectional survey in Northern India
    Manupriya Sharma, Kavita Kumari, Navpreet, Rajneesh Kumari · 2026 · Indian Journal of Pathology and Microbiology
  73. Histopathology-Based Deep Learning for Melanoma PDX Drug-Response Tracking
    Sahil Kapadia, Aria Merrill, Sagar Kapadia · 2025 · IEEE MIT Undergraduate Research Technology Conference (URTC)
  74. Skin Cancer Detection and Classification Using Deep Learning Techniques
    Saritha Suvarna, Ashwin Shenoy M, Nishanth Nagesh Naik, Rahul, Rohan Naik, Pranati Prabhu · 2026 · International Conference on Artificial Intelligence and Data Engineering (AIDE)
  75. Explainable AI framework for melanoma detection using dual-shape masking and composite index
    Akbar Kushanoor, Sanjay K. Sahay · 2026 · Pattern Recognition
  76. Role of Artificial Intelligence in Pancreatic Cyst Diagnosis
    Gaurav Mahajan, Hardeep Kaur, Srinu Deshidi, Surinder Singh Rana · 2026 · Springer eBooks
  77. GPT Fusion: Integrating Convolutional Neural Networks with GPT-5.5 for Melanoma Diagnosis
    Katie L. Frederickson, Dong Li, Samuel E. Adunyah, Qingguo Wang · 2026 · Research Square
  78. CNN-Based Hair Fall Stage and Scalp Disease Classification
    Sushma K, Rishant Bhakta, Ayush, Ayush Anand · 2026 · IEEE Global Symposium on Emerging and Communication Technologies (GSEACT)
  79. GPT Fusion: Reasoning-Based Integration of Specialized Convolutional Neural Networks for Melanoma Diagnosis
    Katie L. Frederickson, Dong Li, Oren D. Edrich, Ashish C. Bhatia, Samuel E. Adunyah, Qingguo Wang · 2026 · Research Square
  80. The Evolving Role of Artificial Intelligence in Dermatology: A Meta-Analysis of Diagnostic Performance, Clinical Applications, and Implementation Challenges (2003–2025)
    Nina Ivanovic, Marius Florentin Popa, Ana-Olivia Toma, Ciprian Nicolae Pilut, Roxana Manuela Fericean, Daniela Crainic, Andreea Nelson Twakor, Daniela-Vasilica Serban, Kersztin Lorett Csiki, Raluca Dumache · 2026 · Diagnostics
  81. Evaluation of diagnostic accuracy of ChatGPT and gemini in identification of basal cell carcinoma in histologic images
    Sabrina Khan, Abigail Grace Hendrie, Omeed Modiri, Jeremy Davis · 2026 · Archives of Dermatological Research
  82. Artificial intelligence applied to surgical pathology in the management of cutaneous melanoma
    Céline Bossard, Y Salhi, Jérôme J. Chetritt · 2026 · La Presse Médicale
  83. Creative thinking in humans and artificial intelligence: A comparative review of neural, molecular, and social mechanisms
    Hiroaki Matsushita, Tei‐ichi Nishiki · 2026 · Neuroscience