H. Peter Soyer

Active 1989–2026

Also published as
H Peter Soyer
241
Papers
22,090
Citations
87
h-index
212
i10-index

Citations

Citations per year for H. Peter Soyer1987: 1 citations1990: 2 citations1991: 2 citations1992: 4 citations1993: 6 citations1994: 3 citations1995: 16 citations1996: 14 citations1997: 22 citations1998: 16 citations1999: 24 citations2000: 40 citations2001: 67 citations2002: 80 citations2003: 66 citations2004: 86 citations2005: 109 citations2006: 92 citations2007: 115 citations2008: 121 citations2009: 134 citations2010: 130 citations2011: 125 citations2012: 175 citations2013: 165 citations2014: 130 citations2015: 136 citations2016: 151 citations2017: 173 citations2018: 284 citations2019: 456 citations2020: 612 citations2021: 694 citations2022: 666 citations2023: 614 citations2024: 836 citations2025: 483 citations2026: 60 citations1988–1989: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 1,430 citing papers, 18.4% of this breakdownAustralia: 506 citing papers, 6.5% of this breakdownItaly: 504 citing papers, 6.5% of this breakdownChina: 474 citing papers, 6.1% of this breakdownGermany: 455 citing papers, 5.9% of this breakdownUnited Kingdom: 453 citing papers, 5.8% of this breakdownSpain: 291 citing papers, 3.8% of this breakdownAustria: 282 citing papers, 3.6% of this breakdownIndia: 272 citing papers, 3.5% of this breakdownFrance: 229 citing papers, 3% of this breakdownCanada: 202 citing papers, 2.6% of this breakdownNetherlands: 150 citing papers, 1.9% of this breakdown
0%18.4%Other 32.4%

Fields

  • Medicine72.5%
  • Biochemistry, Genetics and Molecular Biology8.3%
  • Computer Science6.1%
  • Pharmacology, Toxicology and Pharmaceutics3.4%
  • Engineering2.7%
  • Materials Science1.4%
  • Other5.6%

Topics

  • Cutaneous Melanoma Detection and Management17.3%
  • AI in cancer detection9.1%
  • Nonmelanoma Skin Cancer Studies7.4%
  • Skin Protection and Aging2.7%
  • Artificial Intelligence in Healthcare and Education2.7%
  • melanin and skin pigmentation1.9%
  • Other58.9%

Coauthors

All papers

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  1. Human–computer collaboration for skin cancer recognition

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

  2. 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

  3. 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

  4. A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology

    Authors: , , , , , , , , , , - Scientific Reports 2021 cited by 273

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

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

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

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

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

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

  8. 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

  9. Nanoparticles and microparticles for skin drug delivery

    Authors: , , , , , , , , , , - Advanced Drug Delivery Reviews 2011 cited by 850

  10. An Integrated Microfluidic‐SERS Platform Enables Sensitive Phenotyping of Serum Extracellular Vesicles in Early Stage Melanomas

    Authors: , , , , , , , , - Advanced Functional Materials 2021 cited by 81

  11. Genome-wide association meta-analyses combining multiple risk phenotypes provide insights into the genetic architecture of cutaneous melanoma susceptibility

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Lisa Elefanti, Siranoush Manoukian, Licia Rivoltini, Blair H. Smith, Maria A. Loizidou, Laura Del Regno, Daniela Massi, Mario Mandalà, Kiarash Khosrotehrani, Lars A. Akslen, Christopher I. Amos, Per Arne Andresen, Marie‐Françoise Avril, Esther Azizi, H. Peter Soyer, Véronique Bataille, Bruna Dalmasso, Lisa Bowdler, Kathryn P. Burdon, Wei V. Chen, Veryan Codd, Jamie E. Craig, Tadeusz Dębniak, Mario Falchi, Shenying Fang, Eitan Friedman, Sarah Simi, Pilar Galán, Zaida García‐Casado, Elizabeth M. Gillanders, Scott D. Gordon, Adèle C. Green, Nelleke A. Gruis, Johan Hansson, Mark Harland, Jessica Harris, Per Helsing, Anjali K. Henders, Marko Hočevar, Veronica Höiom, David J. Hunter, Christian Ingvar, Rajiv Kumar, Julie Lang, G.M. Lathrop, Jeffrey E. Lee, Xin Li, Jan Lubiński, Rona M. MacKie, M. Malt, Josep Malvehy, Kerrie McAloney, Hamida Mohamdi, Anders Molven, Eric K. Moses, Rachel Ε. Neale, Srdjan Novaković, Dale R. Nyholt, Håkan Olsson, Nick Orr, Lars G. Fritsche, Joan Anton Puig‐Butille, Abrar A. Qureshi, Graham Radford‐Smith, Juliette A. Randerson‐Moor, Celia Requena, Casey Rowe, Nilesh J. Samani, Marianna Sanna, Dirk Schadendorf and 59 more - Nature Genetics 2020 cited by 239

  12. Artificial Intelligence for the Classification of Pigmented Skin Lesions in Populations with Skin of Color: A Systematic Review

    Authors: , , , , - Dermatology 2023 cited by 45

  13. 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

  14. 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

  15. Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017

    Authors: , , , , , , , , , , , - Journal of the American Academy of Dermatology 2019 cited by 103

  16. Three-Point Checklist of Dermoscopy

    Authors: , , , , , , , , , , , , , - Dermatology 2004 cited by 240

  17. Dermatoscopy of basal cell carcinoma: Morphologic variability of global and local features and accuracy of diagnosis

    Authors: , , , , , , , , , - Journal of the American Academy of Dermatology 2009 cited by 332

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

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

  19. Clinical Perspective of 3D Total Body Photography for Early Detection and Screening of Melanoma

    Authors: , , , , , , - Frontiers in Medicine 2018 cited by 101

  20. A General-Purpose Multimodal Foundation Model for Dermatology

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , - Nature Medicine 2025 cited by 68

  21. Dermoscopy of pigmented skin lesions – a valuable tool for early

    Authors: , - The Lancet Oncology 2001 cited by 392

  22. Standardization of terminology in dermoscopy/dermatoscopy: Results of the third consensus conference of the International Society of Dermoscopy

    Authors: , , , , , , , , , , , , , , , , , , , , - Journal of the American Academy of Dermatology 2016 cited by 310

  23. A stress-induced early innate response causes multidrug tolerance in melanoma

    Authors: , , , , , , , , , , , , , , , , - Oncogene 2014 cited by 174

  24. Early detection of melanoma: a consensus report from the Australian Skin and Skin Cancer Research Centre Melanoma Screening Summit

    Authors: , , , , , , , , , - Australian and New Zealand Journal of Public Health 2020 cited by 58