activity
20232026
most citedDermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

176 citations · 239 across the 6 of their papers we have counts for

collaborators

6 papers

q-bio.GN2026

DNA Methylation Profiling in Melanoma: From Lesion Classification to Therapeutic Stratification

Jana T. Winterstein, Lukas Heinlein, Günter Raddatz +34

DNA methylation provides a stable record of cellular identity, capturing epigenetic programs that distinguish specialized cell states despite a shared genome. Because malignant tra…

cs.AI2024★ 5 cited

Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study

Tirtha Chanda, Sarah Haggenmueller, Tabea-Clara Bucher +19

Artificial intelligence (AI) systems have substantially improved dermatologists' diagnostic accuracy for melanoma, with explainable AI (XAI) systems further enhancing clinicians' c…

eess.IV2024★ 34 cited

Clinical Melanoma Diagnosis with Artificial Intelligence: Insights from a Prospective Multicenter Study

Lukas Heinlein, Roman C. Maron, Achim Hekler +27

Early detection of melanoma, a potentially lethal type of skin cancer with high prevalence worldwide, improves patient prognosis. In retrospective studies, artificial intelligence…

eess.IV2023★ 16 cited

Evaluating Deep Learning-based Melanoma Classification using Immunohistochemistry and Routine Histology: A Three Center Study

Christoph Wies, Lucas Schneider, Sarah Haggenmueller +6

Pathologists routinely use immunohistochemical (IHC)-stained tissue slides against MelanA in addition to hematoxylin and eosin (H&E)-stained slides to improve their accuracy in dia…

eess.IV2023★ 8 cited

Using Multiple Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning: A Prognostic Diagnostic Accuracy Study

Achim Hekler, Roman C. Maron, Sarah Haggenmüller +28

Background: Convolutional neural network (CNN)-based melanoma classifiers face several challenges that limit their usefulness in clinical practice. Objective: To investigate the im…

q-bio.QM2023★ 176 cited

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Tirtha Chanda, Katja Hauser, Sarah Hobelsberger +32

Although artificial intelligence (AI) systems have been shown to improve the accuracy of initial melanoma diagnosis, the lack of transparency in how these systems identify melanoma…