Giacomo Nebbia

11 papers B 1Journal 3Unranked 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
Re-identification of patients from imaging features extracted by foundation models.
npj Digit. Medicine
Giacomo Nebbia, Sourav Kumar, Stephen McNamara, Christopher P. Bridge, J. Peter Campbell, Michael F. Chiang, Naresh Mandava, Praveer Singh, Jayashree Kalpathy-Cramer
2024 — conf
Cycle-GANs Generated Difference Maps to Interpret Race Prediction from Medical Images.
FAIMI/EPIMI@MICCAI
Lakshika Rathi, Giacomo Nebbia, Ken Chang, Sourav Kumar, Aarushi Gupta, Syed Rakin Ahmed, Jay B. Patel, Christopher Clark, Yoga Advaith Veturi, Aaron S. Coyner, Aakanksha Rana, Christopher P. Bridge, Stephen McNamara, J. Peter Campbell, Matthew D. Li, Jayashree Kalpathy-Cramer, Praveer Singh
2024 — conf
Image-caption difficulty for efficient weakly-supervised object detection from in-the-wild data.
CVPR Workshops
Giacomo Nebbia, Adriana Kovashka
2024 — conf
Synonym relations affect object detection learned on vision-language data.
NAACL-HLT (Findings)
Giacomo Nebbia, Adriana Kovashka
2023 B conf
Hypernymization of named entity-rich captions for grounding-based multi-modal pretraining.
ICMR
Giacomo Nebbia, Adriana Kovashka
2023 J jnl
Hypernymization of named entity-rich captions for grounding-based multi-modal pretraining.
CoRR
Giacomo Nebbia, Adriana Kovashka
2022 — conf
Doubling down: sparse grounding with an additional, almost-matching caption for detection-oriented multimodal pretraining.
CVPR Workshops
Giacomo Nebbia, Adriana Kovashka
2021 — conf
Multi-task learning to incorporate clinical knowledge into deep learning for breast cancer diagnosis.
Computer-Aided Diagnosis
Giacomo Nebbia, Dooman Arefan, Margarita L. Zuley, Jules H. Sumkin, Shandong Wu
2021 — conf
Radiomics-Informed Deep Curriculum Learning for Breast Cancer Diagnosis.
MICCAI (5)
Giacomo Nebbia, Saba Dadsetan, Dooman Arefan, Margarita L. Zuley, Jules H. Sumkin, Heng Huang, Shandong Wu
2020 J jnl
Pre-operative Microvascular Invasion Prediction Using Multi-parametric Liver MRI Radiomics.
J. Digit. Imaging
Giacomo Nebbia, Qian Zhang, Dooman Arefan, Xinxiang Zhao, Shandong Wu
2019 — conf
Deep learning of sub-regional breast parenchyma in mammograms for localized breast cancer risk prediction.
Computer-Aided Diagnosis
Giacomo Nebbia, Aly A. Mohamed, Ruimei Chai, Bingjie Zheng, Margarita L. Zuley, Shandong Wu