◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Jorge Cardoso

4 papers hereh-index 11572 citations39 works total

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

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • eess.IV2
  • q-bio.QM2
same name
  • Jorge Cardoso — 11 papers, h 11
  • Jorge Cardoso — 4 papers, h 2
  • Jorge Cardoso — 3 papers, h 3
  • Jorge Cardoso — 2 papers, h 2
  • Jorge Cardoso — 1 paper
  • Jorge Cardoso — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192023
most citedMachine learning and glioma imaging biomarkers

102 citations · 203 across the 4 of their papers we have counts for

collaborators

4 papers

q-bio.QM2023★ 1 cited

Individualized prescriptive inference in ischaemic stroke

Dominic Giles, Chris Foulon, Guilherme Pombo +8

The gold standard in the treatment of ischaemic stroke is set by evidence from randomized controlled trials, based on simple descriptions of presumptively homogeneous populations.…

eess.IV2022★ 1 cited

Augmentation based unsupervised domain adaptation

Mauricio Orbes-Arteaga, Thomas Varsavsky, Lauge Sorensen +5

The insertion of deep learning in medical image analysis had lead to the development of state-of-the art strategies in several applications such a disease classification, as well a…

eess.IV2022★ 99 cited

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation

Reuben Dorent, Aaron Kujawa, Marina Ivory +37

Domain Adaptation (DA) has recently raised strong interests in the medical imaging community. While a large variety of DA techniques has been proposed for image segmentation, most…

q-bio.QM2019★ 102 cited

Machine learning and glioma imaging biomarkers

Thomas Booth, Matthew Williams, Aysha Luis +3

Aim: To review how machine learning (ML) is applied to imaging biomarkers in neuro-oncology, in particular for diagnosis, prognosis, and treatment response monitoring. Materials an…

◍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.