3 citations · 7 across the 12 of their papers we have counts for
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Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification
Skylar Chan, Pranav Kulkarni, Paul H. Yi +1
Quantum machine learning (QML) has the potential for improving the multi-label classification of rare, albeit critical, diseases in large-scale chest x-ray (CXR) datasets due to th…
Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning
Pranav Kulkarni, Adway Kanhere, Harshita Kukreja +3
Generative Adversarial Network (GAN)-based synthesis of fat suppressed (FS) MRIs from non-FS proton density sequences has the potential to accelerate acquisition of knee MRIs. Howe…
Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations
Pranav Kulkarni, Adway Kanhere, Dharmam Savani +4
Curating annotations for medical image segmentation is a labor-intensive and time-consuming task that requires domain expertise, resulting in "narrowly" focused deep learning (DL)…