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Joseph Y. Lo

14 papers hereh-index 337 citations19 works total

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

author position
  • middle author4
  • last author9

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • eess.IV2
  • cs.CL1
  • cs.LG1
  • stat.AP1
same name
  • Joseph Y. Lo — 2 papers, h 2
  • Joseph Y. Lo — 1 paper
  • Joseph Y. Lo — 1 paper, h 3
  • Joseph Y. Lo — 1 paper, h 6
  • Joseph Y. Lo — 1 paper, h 2
  • Joseph Y. Lo — 1 paper, h 2

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
20242026
most citedVirtual Lung Screening Trial (VLST): An In Silico Study Inspired by the National Lung Screening Trial for Lung Cancer Detection

10 citations · 11 across the 14 of their papers we have counts for

collaborators
Showing 2024Show all

3 papers · 1 filter

cs.CV2024★ 1 cited

Reproducible Benchmarking for Lung Nodule Detection and Malignancy Classification Across Multiple Low-Dose CT Datasets

Fakrul Islam Tushar, Avivah Wang, Lavsen Dahal +7

Evaluation of artificial intelligence (AI) models for low-dose CT lung cancer screening is limited by heterogeneous datasets, annotation standards, and evaluation protocols, making…

eess.IV2024★ 10 cited

Virtual Lung Screening Trial (VLST): An In Silico Study Inspired by the National Lung Screening Trial for Lung Cancer Detection

Fakrul Islam Tushar, Liesbeth Vancoillie, Cindy McCabe +16

Clinical imaging trials play a crucial role in advancing medical innovation but are often costly, inefficient, and ethically constrained. Virtual Imaging Trials (VITs) present a so…

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…

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