Introduces the UCSF-PDGM-VQA dataset of 2387 QA pairs from 473 glioma MRI studies and demonstrates that state-of-the-art VLMs exhibit modality collapse on multi-sequence 3D medical images.
Generalist foundation models from a multimodal dataset for 3D computed tomography , ISSN=
4 Pith papers cite this work. Polarity classification is still indexing.
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LoRA fine-tuning of 3-4B SLMs on 162K multi-task radiology data yields strong performance deployable on consumer CPUs at 4-8 tokens/second.
EXACT pre-trains a vision model on 25k CT-report pairs with anatomy-aware weak supervision to output explainable anomaly-aware maps that improve diagnosis, localization, and report generation over prior 3D medical models.
citing papers explorer
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UCSF-PDGM-VQA: Visual Question Answering dataset for brain tumor MRI interpretation
Introduces the UCSF-PDGM-VQA dataset of 2387 QA pairs from 473 glioma MRI studies and demonstrates that state-of-the-art VLMs exhibit modality collapse on multi-sequence 3D medical images.
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RadLite: Multi-Task LoRA Fine-Tuning of Small Language Models for CPU-Deployable Radiology AI
LoRA fine-tuning of 3-4B SLMs on 162K multi-task radiology data yields strong performance deployable on consumer CPUs at 4-8 tokens/second.
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EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT
EXACT pre-trains a vision model on 25k CT-report pairs with anatomy-aware weak supervision to output explainable anomaly-aware maps that improve diagnosis, localization, and report generation over prior 3D medical models.
- RadAgent: A tool-using AI agent for stepwise interpretation of chest computed tomography