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researcher

C. Sako

3 papers hereh-index 182.3k citations72 works total

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

author position
  • middle author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV1
  • cs.LG1
  • eess.IV1

identity via Semantic Scholar / OpenAlex

most citedFederated Learning Enables Big Data for Rare Cancer Boundary Detection

390 citations · 537 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2022★ 390 cited

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Sarthak Pati, Ujjwal Baid, Brandon Edwards +276

Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…

eess.IV2021★ 58 cited

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results

Raghav Mehta, Angelos Filos, Ujjwal Baid +89

Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…

cs.CV2021★ 89 cited

The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification

Ujjwal Baid, Satyam Ghodasara, Suyash Mohan +100

The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR)…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.