Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma
Journal
Nature Communications
ISSN
2041-1723
Date Issued
2024
Author(s)
Tirtha Chanda
Katja Hauser
Sarah Hobelsberger
Tabea-Clara Bucher
Carina Nogueira Garcia
Christoph Wies
Harald Kittler
Philipp Tschandl
Cristian Navarrete-Dechent
Sebastian Podlipnik
Emmanouil Chousakos
Iva Crnaric
Jovana Majstorovic
Linda Alhajwan
Tanya Foreman
Sandra Peternel
Sergei Sarap
İrem Özdemir
Raymond L. Barnhill
Mar Llamas-Velasco
Gabriela Poch
Sören Korsing
Wiebke Sondermann
Frank Friedrich Gellrich
Markus V. Heppt
Michael Erdmann
Sebastian Haferkamp
Konstantin Drexler
Matthias Goebeler
Bastian Schilling
Jochen S. 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 Kalva
Arzu Ferhatosmanoğlu
Aude Beyens
Claudia Pföhler
Dilara Ilhan Erdil
Dobrila Jovanovic
Emoke Racz
Falk G. Bechara
Federico Vaccaro
Florentia Dimitriou
Gunel Rasulova
Hulya Cenk
Irem Yanatma
Isabel Kolm
Isabelle Hoorens
Iskra Petrovska Sheshova
Ivana Jocic
Jana Knuever
Janik Fleißner
Janis Raphael 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
Nicolás 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
Sonia Rodriguez Saa
Sören Hartmann
Stefana Damevska
Stefanie Finck
Stephan Alexander Braun
Tim Hartmann
Tobias Welponer
Tomica Sotirovski
Vanda Bondare-Ansberga
Verena Ahlgrimm-Siess
Verena Gerlinde Frings
Viktor Simeonovski
Zorica Zafirovik
Julia-Tatjana Maul
Saskia Lehr
Marion Wobser
Dirk Debus
Hassan Riad
Manuel P. Pereira
Zsuzsanna Lengyel
Alise Balcere
Amalia Tsakiri
Ralph P. Braun
Titus J. Brinker
Type
journal-article
Abstract
Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists’ decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists’ diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists’ confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists’ willingness to adopt such XAI systems, promoting future use in the clinic.