Original language | English |
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Journal | Journal of Investigative Dermatology |
DOIs | |
Publication status | E-pub ahead of print - 12 Sept 2020 |
Clinically-relevant vulnerabilities of deep machine learning systems for skin cancer diagnosis
Xinyi Du-Harpur, Callum Arthurs, Clarisse Ganier, Rick Woolf, Zainab Laftah, Manpreet Lakhan, Amr Salam, Bo Wan, Fiona M Watt, Nicholas M Luscombe, Magnus D Lynch
- Centre for Stem Cells and Regenerative Medicine, King's College London, Great Maze Pond, London SE1 9RT; The Francis Crick Institute, 1 Midland Road, NW1 1AT; St John's Institute of Dermatology, Guys Hospital, Great Maze Pond, London SE1 9RT Work performed in London, United Kingdom. Electronic address: [email protected].
- Centre for Stem Cells and Regenerative Medicine and Institute for Liver Studies, King's College London, 28th Floor, Tower Wing, Guy's Campus, Great Maze Pond, London SE1 9RT, UK.
- St John's Institute of Dermatology, Guys Hospital, Great Maze Pond, London SE1 9RT Work performed in London, United Kingdom.
- Centre for Stem Cells and Regenerative Medicine, King's College London, Floor 28, Tower Wing, Guy's Hospital, Great Maze Pond, London SE1 9RT, UK; The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.
- The Francis Crick Institute, 1 Midland Road, NW1 1AT; Okinawa Institute of Science & Technology Graduate University, Okinawa, 904-0495, Japan; UCL Genetics Institute, University College London, Gower Street, London, WC1E 6BT, UK.
- Centre for Stem Cells and Regenerative Medicine, King's College London, Great Maze Pond, London SE1 9RT; St John's Institute of Dermatology, Guys Hospital, Great Maze Pond, London SE1 9RT Work performed in London, United Kingdom.
Research output: Contribution to journal › Article › peer-review
18
Citations
(Scopus)