Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data
Recent research revealed the superiority of artificial intelligence over dermatologists to diagnose melanoma from images. However, 30-50% of all melanomas and more than half of those in young patients evolve from initially benign lesions. Despite its high relevance for melanoma screening, neither cl...
Gespeichert in:
| Hauptverfasser: | , , , , , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
8 August 2019
|
| In: |
European journal of cancer
Year: 2019, Jahrgang: 119, Pages: 30-34 |
| ISSN: | 1879-0852 |
| DOI: | 10.1016/j.ejca.2019.07.009 |
| Online-Zugang: | Verlag, Volltext: https://doi.org/10.1016/j.ejca.2019.07.009 Verlag: http://www.sciencedirect.com/science/article/pii/S0959804919304095 
|
| Verfasserangaben: | Wiebke Sondermann, Jochen Sven Utikal, Alexander H. Enk, Dirk Schadendorf, Joachim Klode, Axel Hauschild, Michael Weichenthal, Lars E. French, Carola Berking, Bastian Schilling, Sebastian Haferkamp, Stefan Fröhling, Christof von Kalle, Titus J. Brinker |
MARC
| LEADER | 00000caa a2200000 c 4500 | ||
|---|---|---|---|
| 001 | 1681159090 | ||
| 003 | DE-627 | ||
| 005 | 20220817020544.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 191106s2019 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.ejca.2019.07.009 |2 doi | |
| 035 | |a (DE-627)1681159090 | ||
| 035 | |a (DE-599)KXP1681159090 | ||
| 035 | |a (OCoLC)1341250400 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 084 | |a 33 |2 sdnb | ||
| 100 | 1 | |a Sondermann, Wiebke |e VerfasserIn |0 (DE-588)1198953756 |0 (DE-627)1681162121 |4 aut | |
| 245 | 1 | 0 | |a Prediction of melanoma evolution in melanocytic nevi via artificial intelligence |b A call for prospective data |c Wiebke Sondermann, Jochen Sven Utikal, Alexander H. Enk, Dirk Schadendorf, Joachim Klode, Axel Hauschild, Michael Weichenthal, Lars E. French, Carola Berking, Bastian Schilling, Sebastian Haferkamp, Stefan Fröhling, Christof von Kalle, Titus J. Brinker |
| 264 | 1 | |c 8 August 2019 | |
| 300 | |a 5 | ||
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Gesehen am 06.11.2019 | ||
| 520 | |a Recent research revealed the superiority of artificial intelligence over dermatologists to diagnose melanoma from images. However, 30-50% of all melanomas and more than half of those in young patients evolve from initially benign lesions. Despite its high relevance for melanoma screening, neither clinicians nor computers are yet able to reliably predict a nevus’ oncologic transformation. The cause of this lies in the static nature of lesion presentation in the current standard of care, both for clinicians and algorithms. The status quo makes it difficult to train algorithms (and clinicians) to precisely assess the likelihood of a benign skin lesion to transform into melanoma. In addition, it inhibits the precision of current algorithms since ‘evolution’ image features may not be part of their decision. The current literature reveals certain types of melanocytic nevi (i.e. ‘spitzoid’ or ‘dysplastic’ nevi) and criteria (i.e. visible vasculature) that, in general, appear to have a higher chance to transform into melanoma. However, owing to the cumulative nature of oncogenic mutations in melanoma, a more fine-grained early morphologic footprint is likely to be detectable by an algorithm. In this perspective article, the concept of melanoma prediction is further explored by the discussion of the evolution of melanoma, the concept for training of such a nevi classifier and the implications of early melanoma prediction for clinical practice. In conclusion, the authors believe that artificial intelligence trained on prospective image data could be transformative for skin cancer diagnostics by (a) predicting melanoma before it occurs (i.e. pre-in situ) and (b) further enhancing the accuracy of current melanoma classifiers. Necessary prospective images for this research are obtained via free mole-monitoring mobile apps. | ||
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Deep learning | |
| 650 | 4 | |a Melanoma | |
| 650 | 4 | |a Prediction | |
| 650 | 4 | |a Skin cancer | |
| 700 | 1 | |a Utikal, Jochen |d 1974- |e VerfasserIn |0 (DE-588)1026463750 |0 (DE-627)726765015 |0 (DE-576)371816580 |4 aut | |
| 700 | 1 | |a Enk, Alexander |d 1963- |e VerfasserIn |0 (DE-588)1032757140 |0 (DE-627)739272535 |0 (DE-576)166173517 |4 aut | |
| 700 | 1 | |a Fröhling, Stefan |d 1969- |e VerfasserIn |0 (DE-588)120890046 |0 (DE-627)080950302 |0 (DE-576)188733930 |4 aut | |
| 700 | 1 | |a Kalle, Christof von |d 1962- |e VerfasserIn |0 (DE-588)1036481115 |0 (DE-627)75107926X |0 (DE-576)168957396 |4 aut | |
| 700 | 1 | |a Brinker, Titus Josef |d 1990- |e VerfasserIn |0 (DE-588)1156309395 |0 (DE-627)1018860487 |0 (DE-576)502097434 |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t European journal of cancer |d Amsterdam [u.a.] : Elsevier, 1992 |g 119(2019), Seite 30-34 |w (DE-627)266883400 |w (DE-600)1468190-0 |w (DE-576)090954173 |x 1879-0852 |7 nnas |a Prediction of melanoma evolution in melanocytic nevi via artificial intelligence A call for prospective data |
| 773 | 1 | 8 | |g volume:119 |g year:2019 |g pages:30-34 |g extent:5 |a Prediction of melanoma evolution in melanocytic nevi via artificial intelligence A call for prospective data |
| 787 | 0 | 8 | |i Errata |a Sondermann, Wiebke |t Corrigendum to ‘Prediction of melanoma evolution in melanocytic nevi via artificial intelligence |d 2019 |w (DE-627)168927722X |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.ejca.2019.07.009 |x Verlag |x Resolving-System |3 Volltext |
| 856 | 4 | 0 | |u http://www.sciencedirect.com/science/article/pii/S0959804919304095 |x Verlag |
| 951 | |a AR | ||
| 992 | |a 20191106 | ||
| 993 | |a Article | ||
| 994 | |a 2019 | ||
| 998 | |g 1026463750 |a Utikal, Jochen |m 1026463750:Utikal, Jochen |d 60000 |e 60000PU1026463750 |k 0/60000/ |p 2 | ||
| 998 | |g 1156309395 |a Brinker, Titus Josef |m 1156309395:Brinker, Titus Josef |d 910000 |d 911300 |e 910000PB1156309395 |e 911300PB1156309395 |k 0/910000/ |k 1/910000/911300/ |p 14 |y j | ||
| 998 | |g 1036481115 |a Kalle, Christof von |m 1036481115:Kalle, Christof von |d 50000 |e 50000PK1036481115 |k 0/50000/ |p 13 | ||
| 998 | |g 120890046 |a Fröhling, Stefan |m 120890046:Fröhling, Stefan |d 50000 |e 50000PF120890046 |k 0/50000/ |p 12 | ||
| 998 | |g 1032757140 |a Enk, Alexander |m 1032757140:Enk, Alexander |d 910000 |d 911300 |e 910000PE1032757140 |e 911300PE1032757140 |k 0/910000/ |k 1/910000/911300/ |p 3 | ||
| 999 | |a KXP-PPN1681159090 |e 3538041725 | ||
| BIB | |a Y | ||
| SER | |a journal | ||
| JSO | |a {"relHost":[{"origin":[{"dateIssuedDisp":"1992-","publisher":"Elsevier ; Pergamon Press","publisherPlace":"Amsterdam [u.a.] ; [Erscheinungsort nicht ermittelbar]","dateIssuedKey":"1992"}],"corporate":[{"role":"isb","display":"European Organization for Research on Treatment of Cancer"},{"display":"European Association for Cancer Research","role":"isb"},{"role":"isb","display":"European School of Oncology"}],"title":[{"title":"European journal of cancer","title_sort":"European journal of cancer"}],"id":{"eki":["266883400"],"zdb":["1468190-0"],"issn":["1879-0852"]},"part":{"year":"2019","extent":"5","pages":"30-34","volume":"119","text":"119(2019), Seite 30-34"},"note":["Gesehen am 21.03.24","Ungezählte Beil.: Supplement"],"recId":"266883400","disp":"Prediction of melanoma evolution in melanocytic nevi via artificial intelligence A call for prospective dataEuropean journal of cancer","language":["eng"],"titleAlt":[{"title":"EJC online"}],"pubHistory":["28.1992 -"],"type":{"media":"Online-Ressource","bibl":"periodical"}}],"note":["Gesehen am 06.11.2019"],"physDesc":[{"extent":"5 S."}],"type":{"bibl":"article-journal","media":"Online-Ressource"},"id":{"doi":["10.1016/j.ejca.2019.07.009"],"eki":["1681159090"]},"language":["eng"],"title":[{"title":"Prediction of melanoma evolution in melanocytic nevi via artificial intelligence","subtitle":"A call for prospective data","title_sort":"Prediction of melanoma evolution in melanocytic nevi via artificial intelligence"}],"person":[{"role":"aut","family":"Sondermann","display":"Sondermann, Wiebke","given":"Wiebke"},{"role":"aut","family":"Utikal","given":"Jochen","display":"Utikal, Jochen"},{"role":"aut","given":"Alexander","display":"Enk, Alexander","family":"Enk"},{"family":"Fröhling","given":"Stefan","display":"Fröhling, Stefan","role":"aut"},{"role":"aut","family":"Kalle","display":"Kalle, Christof von","given":"Christof von"},{"display":"Brinker, Titus Josef","given":"Titus Josef","family":"Brinker","role":"aut"}],"recId":"1681159090","name":{"displayForm":["Wiebke Sondermann, Jochen Sven Utikal, Alexander H. Enk, Dirk Schadendorf, Joachim Klode, Axel Hauschild, Michael Weichenthal, Lars E. French, Carola Berking, Bastian Schilling, Sebastian Haferkamp, Stefan Fröhling, Christof von Kalle, Titus J. Brinker"]},"origin":[{"dateIssuedDisp":"8 August 2019","dateIssuedKey":"2019"}]} | ||
| SRT | |a SONDERMANNPREDICTION8201 | ||