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Vincent M. D'Anniballe

3 papers hereh-index 5194 citations18 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 3 papers where every author was matched, so the position is known.

fields
  • eess.IV2
  • cs.CV1

identity via Semantic Scholar / OpenAlex

activity
20202024
most citedWeakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features

7 citations · 7 across the 3 of their papers we have counts for

collaborators

3 papers

eess.IV2024

What limits performance of weakly supervised deep learning for chest CT classification?

Fakrul Islam Tushar, Vincent M. D'Anniballe, Geoffrey D. Rubin +1

Weakly supervised learning with noisy data has drawn attention in the medical imaging community due to the sparsity of high-quality disease labels. However, little is known about t…

eess.IV2022

Co-occurring Diseases Heavily Influence the Performance of Weakly Supervised Learning Models for Classification of Chest CT

Fakrul Islam Tushar, Vincent M. D'Anniballe, Geoffrey D. Rubin +2

Despite the potential of weakly supervised learning to automatically annotate massive amounts of data, little is known about its limitations for use in computer-aided diagnosis (CA…

cs.CV2020★ 7 cited

Weakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features

Anindo Saha, Fakrul I. Tushar, Khrystyna Faryna +5

Weakly supervised disease classification of CT imaging suffers from poor localization owing to case-level annotations, where even a positive scan can hold hundreds to thousands of…

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