◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Francesco Ciompi

3 papers here

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

author position
  • middle author2
  • last author1

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

fields
  • cs.CV1
  • q-bio.QM1
  • q-bio.TO1
ORCID 0000-0001-8327-9606

identity via Semantic Scholar / OpenAlex

most citedUncertainty-guided annotation enhances segmentation with the human-in-the-loop

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

collaborators

3 papers

q-bio.QM2025

A Multicentric Dataset for Training and Benchmarking Breast Cancer Segmentation in H&E Slides

Carlijn Lems, Leslie Tessier, John-Melle Bokhorst +18

Automated semantic segmentation of whole-slide images (WSIs) stained with hematoxylin and eosin (H&E) is essential for large-scale artificial intelligence-based biomarker analysis…

cs.CV2024★ 1 cited

Uncertainty-guided annotation enhances segmentation with the human-in-the-loop

Nadieh Khalili, Joey Spronck, Francesco Ciompi +2

Deep learning algorithms, often critiqued for their 'black box' nature, traditionally fall short in providing the necessary transparency for trusted clinical use. This challenge is…

q-bio.TO2024★ 1 cited

Hitchhiker's guide to cancer-associated lymphoid aggregates in histology images: manual and deep learning-based quantification approaches

Karina Silina, Francesco Ciompi

Quantification of lymphoid aggregates including tertiary lymphoid structures with germinal centers in histology images of cancer is a promising approach for developing prognostic a…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.