4 citations · 9 across the 15 of their papers we have counts for
6 papers · 1 filter
Fed-ADApt: Federated Anytime Depth Adaptation for Resource-Aware Medical Image Segmentation
Abhijeet Parida, Zhifan Jiang, Pooneh Roshanitabrizi +6
Federated learning (FL) enables collaborative training of medical image segmentation models without sharing raw patient data, yet existing approaches assume a homogeneous compute b…
Evaluating Biomedical Reranking for LLM-Based Question Answering over Longitudinal Clinical Notes
Maryam Shahbaz Ali, Laura B. Strachan, Caitlin Sherman +3
Patient-specific clinical question answering requires locating the right evidence within long, heterogeneous longitudinal clinical records in which relevant facts may be scattered…
A Multi-Dimensional Clustering Approach for Identifying Inborn Errors of Immunity
Nishad Kulkarni, Alexandra K. Martinson, Nicholas L. Rider +2
Rare diseases such as inborn errors of immunity (IEI) require early diagnosis to prevent end organ damage and improve quality of life. Hurdles in accessing and curating large scale…
VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignment
Amy Makawana, Abhijeet Parida, Marius George Linguraru +2
Self-supervised learning (SSL) has advanced medical image analysis be enabling learning form large unlabelled data. However, in brain magnetic resonance imaging (MRI), most 3D mode…
LUMEN: Longitudinal Multi-Modal Radiology Model for Prognosis and Diagnosis
Zhifan Jiang, Dong Yang, Vishwesh Nath +7
Large vision-language models (VLMs) have evolved from general-purpose applications to specialized use cases such as in the clinical domain, demonstrating potential for decision sup…
FeTTL: Federated Template and Task Learning for Multi-Institutional Medical Imaging
Abhijeet Parida, Antonia Alomar, Zhifan Jiang +7
Federated learning enables collaborative model training across geographically distributed medical centers while preserving data privacy. However, domain shifts and heterogeneity in…