Harald Kittler

Active 1997–2026

119
Papers
18,540
Citations
65
h-index
98
i10-index

Citations

Citations per year for Harald Kittler1981: 1 citations1986: 2 citations1991: 2 citations1992: 4 citations1997: 1 citations1998: 4 citations1999: 6 citations2000: 17 citations2001: 46 citations2002: 47 citations2003: 69 citations2004: 79 citations2005: 74 citations2006: 63 citations2007: 73 citations2008: 77 citations2009: 104 citations2010: 73 citations2011: 97 citations2012: 100 citations2013: 81 citations2014: 83 citations2015: 86 citations2016: 100 citations2017: 166 citations2018: 291 citations2019: 437 citations2020: 680 citations2021: 954 citations2022: 894 citations2023: 1,072 citations2024: 1,490 citations2025: 1,178 citations2026: 325 citations2027: 1 citations1982–1985: no citations, so these years are not shown1987–1990: no citations, so these years are not shown1993–1996: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 1,397 citing papers, 14.8% of this breakdownChina: 1,259 citing papers, 13.3% of this breakdownIndia: 506 citing papers, 5.4% of this breakdownUnited Kingdom: 498 citing papers, 5.3% of this breakdownGermany: 486 citing papers, 5.2% of this breakdownItaly: 459 citing papers, 4.9% of this breakdownAustralia: 344 citing papers, 3.6% of this breakdownSpain: 294 citing papers, 3.1% of this breakdownCanada: 261 citing papers, 2.8% of this breakdownAustria: 250 citing papers, 2.6% of this breakdownFrance: 228 citing papers, 2.4% of this breakdownSaudi Arabia: 178 citing papers, 1.9% of this breakdown
0%14.8%Other 34.7%

Fields

  • Medicine62.8%
  • Computer Science25.6%
  • Biochemistry, Genetics and Molecular Biology2.7%
  • Engineering2.6%
  • Immunology and Microbiology1.6%
  • Neuroscience1.3%
  • Other3.4%

Topics

  • Cutaneous Melanoma Detection and Management18.1%
  • AI in cancer detection14.9%
  • Nonmelanoma Skin Cancer Studies6.4%
  • Advanced Neural Network Applications2.9%
  • Artificial Intelligence in Healthcare and Education2.4%
  • COVID-19 diagnosis using AI2.2%
  • Other53.1%

Coauthors

All papers

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  1. The HAM10000 Dataset: A Large Collection of Multi-Source Dermatoscopic Images of Common Pigmented Skin Lesions

    Authors: , , - Scientific Data 2018 cited by 3,184

  2. Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

    Authors: , , , , , , , , , , , - arXiv (Cornell University), CoRR 2019 cited by 1,182

  3. Human–computer collaboration for skin cancer recognition

    Authors: , , , , , , , , , , , , , , , - Nature Medicine 2020 cited by 912

  4. Diagnostic accuracy of dermoscopy

    Authors: , , , - The Lancet Oncology 2002 cited by 1,317

  5. Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Jochen Utikal, Kamran Ghoreschi, Stefan Fröhling, Eva Krieghoff‐Henning, Alexander Salava, Alexander Thiem, Alexandris Dimitrios, Amr Mohammad Ammar, Ana Sanader Vučemilović, Andrea Miyuki Yoshimura, Andzelka Ilieva, Anja Gesierich, Antonia Reimer‐Taschenbrecker, Antonios G.A. Kolios, Arturs Kaļva, Arzu Ferhatosmanoğlu, Aude Beyens, Claudia Pföhler, Dilara Ilhan Erdil, Dobrila Jovanovic, Emöke Rácz, Falk G. Bechara, Federico Vaccaro, Florentia Dimitriou, Günel Rasulova, Hülya Cenk, Irem Yanatma, Isabel Kolm, Isabelle Hoorens, Iskra Petrovska Sheshova, Ivana Jocic, Jana Knuever, Janik Fleißner, Janis Thamm, Johan Dahlberg, Juan José Lluch‐Galcerá, Juan Sebastián Andreani Figueroa, Julia Holzgruber, Julia Welzel, Katerina Damevska, Kristine Elisabeth Mayer, Lara Valeska Maul, Laura Garzona-Navas, Laura Isabell Bley, Laurenz Schmitt, Lena Reipen, Lidia Shafik, Lidija Petrovska, Linda Golle, Luise Jopen, Magda Gogilidze, Maria Rosa Burg, Martha Alejandra Morales‐Sánchez, Martyna Sławińska, Miriam Mengoni, Miroslav Dragolov, N. Iglesias-Pena, Nina Booken, Nkechi Anne Enechukwu, Oana‐Diana Persa, Olumayowa Abimbola Oninla, Panagiota Theofilogiannakou, Paula Kage, Roque Rafael Oliveira Neto, Rosario Peralta, Rym Afiouni, Sandra Schuh, Saskia Schnabl-Scheu, Seçil Vural, Sharon Hudson and 24 more - Nature Communications 2024 cited by 151

  6. Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Konstantinos Liopyris, Mar Llamas‐Velasco, Josep Malvehy, Friedegund Meier, F. Max Müller, Alexander A. Navarini, Cristián Navarrete‐Dechent, Antonio Perasole, Gabriela Poch, Sebastián Podlipnik, Luis Requena, Veronica Rotemberg, Andrea Saggini, Omar P. Sangüeza, Carlos Santonja, Dirk Schadendorf, Bastian Schilling, Max Schlaak, Justin Gabriel Schlager, Mildred Sergon, Wiebke Sondermann, H. Peter Soyer, Hans Starz, Wilhelm Stolz, Esmeralda Vale, Wolfgang Weyers, Alexander Zink, Eva Krieghoff‐Henning, Jakob Nikolas Kather, Christof von Kalle, Daniel B. Lipka, Stefan Fröhling, Axel Hauschild, Harald Kittler, Titus J. Brinker - European Journal of Cancer 2021 cited by 247

  7. Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , - The Lancet Oncology 2019 cited by 539

  8. Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)

    Authors: , , , , , , , , , , - IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) 2018 cited by 297

  9. A reinforcement learning model for AI-based decision support in skin cancer

    Authors: , , , , , , , , , , , , , , , , - Nature Medicine 2023 cited by 96

  10. Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks

    Authors: , , , , , , , , , , , , , , , , , , , , , , - JAMA Dermatology 2018 cited by 331

  11. Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge

    Authors: , , , , , , , , , , , , , , , , , - The Lancet Digital Health 2022 cited by 119

  12. Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology

    Authors: , , , , , , , , , , , , , , , , , , - JAMA Dermatology 2021 cited by 149

  13. Dermoscopy of pigmented skin lesions: Results of a consensus meeting via the Internet

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Brian Katz, Robert O. Kenet, Harald Kittler, J. Kreusch, Josep Malvehy, Giampiero Mazzocchetti, Margaret Oliviero, Fezal zdemir, Ketty Peris, Roberto Perotti, Ana M. Perusquia, Maria Antonietta Pizzichetta, Susana Puig, Babar Rao, Pietro Rubegni, Toshiaki Saida, Massimiliano Scalvenzi, Stefania Seidenari, Ignazio Stanganelli, Masaru Tanaka, Karin Westerhoff, Ingrid Wolf, Otto Braun‐Falco, Helmut Kerl, Takeji Nishikawa, Klaus Wolff, Alfred W. Kopf - Journal of the American Academy of Dermatology 2003 cited by 1,204

  14. Artificial Intelligence in Skin Cancer Diagnosis: A Reality Check

    Authors: , , , , , - Journal of Investigative Dermatology 2023 cited by 103

  15. Comparison of humans versus mobile phone-powered artificial intelligence for the diagnosis and management of pigmented skin cancer in secondary care: a multicentre, prospective, diagnostic, clinical trial

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Susanne Richter, Katharina Silic, Thomas Silly, Michael Skoll, Julia Tittes, Philipp Weber, Wolfgang J. Weninger, Doris Weiss, Ping Woo-Sampson, Catherine Zilberg, Harald Kittler - The Lancet Digital Health 2023 cited by 74

  16. Automated Melanoma Recognition

    Authors: , , , , , - IEEE Transactions on Medical Imaging, IEEE Trans. Medical Imaging 2001 cited by 636

  17. The SLICE-3D dataset: 400,000 skin lesion image crops extracted from 3D TBP for skin cancer detection

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Georgios Theocharis, Ayesha Vos, Jochen Weber, Veronica Rotemberg - Scientific Data 2024 cited by 41

  18. Accuracy of Computer-Aided Diagnosis of Melanoma

    Authors: , , , , - JAMA Dermatology 2019 cited by 125

  19. Position statement of the EADV Artificial Intelligence (AI) Task Force on AI‐assisted smartphone apps and web‐based services for skin disease

    Authors: , , , , , , , , , , , , , , , , , , , , - Journal of the European Academy of Dermatology and Venereology 2023 cited by 52

  20. Domain-specific classification-pretrained fully convolutional network encoders for skin lesion segmentation

    Authors: , , - Computers in Biology and Medicine, Comput. Biol. Medicine 2018 cited by 114

  21. Derm1M: A Million-Scale Vision-Language Dataset Aligned with Clinical Ontology Knowledge for Dermatology

    Authors: , , , , , , , - IEEE/CVF International Conference on Computer Vision (ICCV) 2025 cited by 17

  22. Attitudes towards artificial intelligence within dermatology: an international online survey

    Authors: , , , , , , - British Journal of Dermatology 2020 cited by 92

  23. Skin lesions of face and scalp – Classification by a market-approved convolutional neural network in comparison with 64 dermatologists

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Cécile Chabbert, Julie Labarthe, Eveline Decoster, Teresa Deinlein, Michèle Dobler, Daphnée Dumon, Steffen Emmert, Julie Gachon-Buffet, Mikhail Gusarov, Franziska Hartmann, Julia Hartmann, Anke Herrmann, Isabelle Hoorens, Eva Hulstaert, Raimonds Karls, Andreea Kolonte, Christian Kromer, Aimilios Lallas, Céline Le Blanc Vasseux, Annabelle Levy-Roy, Pawel Majenka, Marine Marc, Veronique Martin Bourret, Nadège Michelet-Brunacci, Christina Mitteldorf, Jean Paroissien, Camille Picard, Diana Plise, V. Reymann, Fabrice Ribeaudeau, Pauline Richez, Hélène Roche Plaine, D. Salik, Elke Sattler, Sarah K. Schäfer, Roland Schneiderbauer, Thierry Secchi, K. Talour, Lukas Trennheuser, Alexander Wald, Priscila Wölbing, P Zukervar - European Journal of Cancer 2020 cited by 44

  24. Accuracy of dermatoscopy for the diagnosis of nonpigmented cancers of the skin

    Authors: , , , , , , , , , , , , , , , , , , , , , - Journal of the American Academy of Dermatology 2017 cited by 125