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researcher

Maelys Solal

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • eess.IV1

identity via Semantic Scholar / OpenAlex

activity
20232025
most citedLeveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET

3 citations · 3 across the 2 of their papers we have counts for

collaborators

3 papers

cs.CV2025

False Promises in Medical Imaging AI? Assessing Validity of Outperformance Claims

Evangelia Christodoulou, Annika Reinke, Pascaline Andrè +23

Performance comparisons are fundamental in medical imaging Artificial Intelligence (AI) research, often driving claims of superiority based on relative improvements in common perfo…

cs.CV2024

Confidence intervals uncovered: Are we ready for real-world medical imaging AI?

Evangelia Christodoulou, Annika Reinke, Rola Houhou +19

Medical imaging is spearheading the AI transformation of healthcare. Performance reporting is key to determine which methods should be translated into clinical practice. Frequently…

eess.IV2023★ 3 cited

Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET

Maëlys Solal, Ravi Hassanaly, Ninon Burgos

Unsupervised anomaly detection is a popular approach for the analysis of neuroimaging data as it allows to identify a wide variety of anomalies from unlabelled data. It relies on b…

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