Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.

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MARC

Haenssle, H AHeidelberg University (author)

Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.

Article/chapterEnglish2018

Publisher, publication year, extent ...

Elsevier BV,2018

Numbers

LIBRIS-ID:oai:gup.ub.gu.se/302370
https://gup.ub.gu.se/publication/302370URI
https://doi.org/10.1093/annonc/mdy166DOI
https://lup.lub.lu.se/record/45bd6566-8465-4d6d-b3fd-c04bb76bd276URI

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Language:English

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SwePubSwePub

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Subject category:ref swepub-contenttype
Subject category:art swepub-publicationtype

Notes

Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking.Google's Inception v4 CNN architecture was trained and validated using dermoscopic images and corresponding diagnoses. In a comparative cross-sectional reader study a 100-image test-set was used (level-I: dermoscopy only; level-II: dermoscopy plus clinical information and images). Main outcome measures were sensitivity, specificity and area under the curve (AUC) of receiver operating characteristics (ROC) for diagnostic classification (dichotomous) of lesions by the CNN versus an international group of 58 dermatologists during level-I or -II of the reader study. Secondary end points included the dermatologists' diagnostic performance in their management decisions and differences in the diagnostic performance of dermatologists during level-I and -II of the reader study. Additionally, the CNN's performance was compared with the top-five algorithms of the 2016 International Symposium on Biomedical Imaging (ISBI) challenge.In level-I dermatologists achieved a mean (±standard deviation) sensitivity and specificity for lesion classification of 86.6% (±9.3%) and 71.3% (±11.2%), respectively. More clinical information (level-II) improved the sensitivity to 88.9% (±9.6%, P=0.19) and specificity to 75.7% (±11.7%, P<0.05). The CNN ROC curve revealed a higher specificity of 82.5% when compared with dermatologists in level-I (71.3%, P<0.01) and level-II (75.7%, P<0.01) at their sensitivities of 86.6% and 88.9%, respectively. The CNN ROC AUC was greater than the mean ROC area of dermatologists (0.86 versus 0.79, P<0.01). The CNN scored results close to the top three algorithms of the ISBI 2016 challenge.For the first time we compared a CNN's diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians' experience, they may benefit from assistance by a CNN's image classification.This study was registered at the German Clinical Trial Register (DRKS-Study-ID: DRKS00013570; https://www.drks.de/drks_web/).

Subject headings and genre

MEDICIN OCH HÄLSOVETENSKAP Klinisk medicin Dermatologi och venereologi hsv//swe
MEDICAL AND HEALTH SCIENCES Clinical Medicine Dermatology and Venereal Diseases hsv//eng
MEDICIN OCH HÄLSOVETENSKAP Klinisk medicin Radiologi och bildbehandling hsv//swe
MEDICAL AND HEALTH SCIENCES Clinical Medicine Radiology, Nuclear Medicine and Medical Imaging hsv//eng
MEDICIN OCH HÄLSOVETENSKAP Klinisk medicin Cancer och onkologi hsv//swe
MEDICAL AND HEALTH SCIENCES Clinical Medicine Cancer and Oncology hsv//eng
Clinical Competence
Cross-Sectional Studies
Deep Learning
Dermatologists
statistics & numerical data
Dermoscopy
Humans
Image Processing
Computer-Assisted
methods
statistics & numerical data
International Cooperation
Melanoma
diagnostic imaging
ROC Curve
Retrospective Studies
Skin
diagnostic imaging
Skin Neoplasms
diagnostic imaging
melanoma
melanocytic nevi
dermoscopy
deep learning convolutional neural network
computer algorithm
automated melonoma detection

Added entries (persons, corporate bodies, meetings, titles ...)

Fink, CHeidelberg University (author)
Schneiderbauer, RHeidelberg University (author)
Toberer, FHeidelberg University (author)
Buhl, TUniversity of Göttingen (author)
Blum, A (author)
Kalloo, AMemorial Sloan-Kettering Cancer Center (author)
Hassen, A Ben HadjUniversity of Passau (author)
Thomas, LClaude Bernard University Lyon 1 (author)
Enk, AHeidelberg University (author)
Uhlmann, LHeidelberg University (author)
Alt, Christina (author)
Arenbergerova, Monika (author)
Bakos, Renato (author)
Baltzer, Anne (author)
Bertlich, Ines (author)
Blum, Andreas (author)
Bokor-Billmann, Therezia (author)
Bowling, Jonathan (author)
Braghiroli, Naira (author)
Braun, Ralph (author)
Buder-Bakhaya, Kristina (author)
Buhl, Timo (author)
Cabo, Horacio (author)
Cabrijan, Leo (author)
Cevic, Naciye (author)
Classen, Anna (author)
Deltgen, David (author)
Fink, Christine (author)
Georgieva, Ivelina (author)
Hakim-Meibodi, Lara-Elena (author)
Hanner, Susanne (author)
Hartmann, Franziska (author)
Hartmann, Julia (author)
Haus, Georg (author)
Hoxha, Elti (author)
Karls, Raimonds (author)
Koga, Hiroshi (author)
Kreusch, Jürgen (author)
Lallas, Aimilios (author)
Majenka, Pawel (author)
Marghoob, Ash (author)
Massone, Cesare (author)
Mekokishvili, Lali (author)
Mestel, Dominik (author)
Meyer, Volker (author)
Neuberger, Anna (author)
Nielsen, KariLund University,Lunds universitet,Dermatologi och venereologi, Lund,Sektion III,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Dermatology and Venereology (Lund),Section III,Department of Clinical Sciences, Lund,Faculty of Medicine(Swepub:lu)med-kni (author)
Oliviero, Margaret (author)
Pampena, Riccardo (author)
Paoli, John,1975Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper, Avdelningen för dermatologi och venereologi,Institute of Clinical Sciences, Department of Dermatology and Venereology(Swepub:gu)xpaojo (author)
Pawlik, Erika (author)
Rao, Barbar (author)
Rendon, Adriana (author)
Russo, Teresa (author)
Sadek, Ahmed (author)
Samhaber, Kinga (author)
Schneiderbauer, Roland (author)
Schweizer, Anissa (author)
Toberer, Ferdinand (author)
Trennheuser, Lukas (author)
Vlahova, Lyobomira (author)
Wald, Alexander (author)
Winkler, Julia (author)
Wölbing, Priscila (author)
Zalaudek, Iris (author)
Heidelberg UniversityUniversity of Göttingen (creator_code:org_t)
Reader study level-I and level-II Groups

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By the author/editor: Haenssle, H A; Fink, C; Schneiderbauer, ...; Toberer, F; Buhl, T; Blum, A; show more...; Kalloo, A; Hassen, A Ben Ha ...; Thomas, L; Enk, A; Uhlmann, L; Alt, Christina; Arenbergerova, M ...; Bakos, Renato; Baltzer, Anne; Bertlich, Ines; Blum, Andreas; Bokor-Billmann, ...; Bowling, Jonatha ...; Braghiroli, Nair ...; Braun, Ralph; Buder-Bakhaya, K ...; Buhl, Timo; Cabo, Horacio; Cabrijan, Leo; Cevic, Naciye; Classen, Anna; Deltgen, David; Fink, Christine; Georgieva, Iveli ...; Hakim-Meibodi, L ...; Hanner, Susanne; Hartmann, Franzi ...; Hartmann, Julia; Haus, Georg; Hoxha, Elti; Karls, Raimonds; Koga, Hiroshi; Kreusch, Jürgen; Lallas, Aimilios; Majenka, Pawel; Marghoob, Ash; Massone, Cesare; Mekokishvili, La ...; Mestel, Dominik; Meyer, Volker; Neuberger, Anna; Nielsen, Kari; Oliviero, Margar ...; Pampena, Riccard ...; Paoli, John, 197 ...; Pawlik, Erika; Rao, Barbar; Rendon, Adriana; Russo, Teresa; Sadek, Ahmed; Samhaber, Kinga; Schneiderbauer, ...; Schweizer, Aniss ...; Toberer, Ferdina ...; Trennheuser, Luk ...; Vlahova, Lyobomi ...; Wald, Alexander; Winkler, Julia; Wölbing, Priscil ...; Zalaudek, Iris; show less...

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MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Clinical Medicin ...; and Dermatology and ...

MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Clinical Medicin ...; and Radiology Nuclea ...

MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Clinical Medicin ...; and Cancer and Oncol ...

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