output
20162025
most citedDermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

176 citations

16 papers

cs.CE2025★ 3 cited

Volumetric Non-Invasive Cardiac Mapping for Accessible Global Arrhythmia Characterization

Jorge Vicente-Puig, Judit Chamorro-Servent, Ernesto Zacur +10

Cardiac arrhythmias are a major cause of morbidity and mortality increasing the risk of stroke, heart failure, and sudden cardiac death. Imageless electrocardiographic imaging (ECG…

eess.IV2025★ 3 cited

Automatic quality control in multi-centric fetal brain MRI super-resolution reconstruction

Thomas Sanchez, Vladyslav Zalevskyi, Angeline Mihailov +7

Quality control (QC) has long been considered essential to guarantee the reliability of neuroimaging studies. It is particularly important for fetal brain MRI, where acquisitions a…

cs.LG2023★ 3 cited

Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised learning

Filippo Corponi, Bryan M. Li, Gerard Anmella +13

Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood di…

eess.IV2023★ 15 cited

FetMRQC: a robust quality control system for multi-centric fetal brain MRI

Thomas Sanchez, Oscar Esteban, Yvan Gomez +8

Fetal brain MRI is becoming an increasingly relevant complement to neurosonography for perinatal diagnosis, allowing fundamental insights into fetal brain development throughout ge…

eess.IV2023★ 8 cited

FetMRQC: Automated Quality Control for fetal brain MRI

Thomas Sanchez, Oscar Esteban, Yvan Gomez +2

Quality control (QC) has long been considered essential to guarantee the reliability of neuroimaging studies. It is particularly important for fetal brain MRI, where large and unpr…

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…