9 citations · 15 across the 9 of their papers we have counts for
6 papers · 1 filter
Multi-Site Real-World Performance of Commercial AI for Pulmonary and Incidental Pulmonary Embolism Detection
Aawez Mansuri, Mohammadreza Chavoshi, Theodorus Dapamede +13
Pulmonary embolism (PE) is a leading cause of cardiovascular mortality, yet the real-world performance of FDA-cleared AI detection models remains incompletely characterized. We ret…
Solving the Needle-in-a-Haystack Problem in Mammography Vision-Language Model with Differentiable Subset Sampling
Young Seok Jeon, Beatrice Brown-Mulry, Rohan Satya Isaac +5
There is growing interest in adopting CLIP-style vision--language model (VLM) pretraining for mammography. However, models that directly employ the standard CLIP architecture and t…
MultiMedVision: Multi-Modal Medical Vision Framework
Frank Li, Bardia Khosravi, Mohammadreza Chavoshi +5
Multi-modal medical imaging enables comprehensive diagnostics, yet current foundation models process 2D (e.g. X-ray) and 3D (e.g. CT) data with separate, dimensionality-specific ar…
Feature Quality and Adaptability of Medical Foundation Models: A Comparative Evaluation for Radiographic Classification and Segmentation
Frank Li, Theo Dapamede, Mohammadreza Chavoshi +12
Foundation models (FMs) promise to generalize medical imaging, but their effectiveness varies. It remains unclear how pre-training domain (medical vs. general), paradigm (e.g., tex…
Evaluating Vision Language Models (VLMs) for Radiology: A Comprehensive Analysis
Frank Li, Hari Trivedi, Bardia Khosravi +8
Foundation models, trained on vast amounts of data using self-supervised techniques, have emerged as a promising frontier for advancing artificial intelligence (AI) applications in…
Emory Knee Radiograph (MRKR) Dataset
Brandon Price, Jason Adleberg, Kaesha Thomas +6
The Emory Knee Radiograph (MRKR) dataset is a large, demographically diverse collection of 503,261 knee radiographs from 83,011 patients, 40% of which are African American. This da…