output
20192025
most citedDermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

176 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2023Show all

3 papers · 1 filter

stat.ML2023★ 12 cited

Gradient and Uncertainty Enhanced Sequential Sampling for Global Fit

Sven Lämmle, Can Bogoclu, Kevin Cremanns +1

Surrogate models based on machine learning methods have become an important part of modern engineering to replace costly computer simulations. The data used for creating a surrogat…

stat.AP2023★ 7 cited

From RNA sequencing measurements to the final results: a practical guide to navigating the choices and uncertainties of gene set analysis

Milena Wünsch, Christina Sauer, Patrick Callahan +2

Gene set analysis, a popular approach for analyzing high-throughput gene expression data, aims to identify sets of related genes that show significantly enriched or depleted expres…

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…