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20242026
most citedEnhancing chest X-ray datasets with privacy-preserving large language models and multi-type annotations: a data-driven approach for improved classification

7 citations · 7 across the 5 of their papers we have counts for

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cs.AI2024

How Well Do Multi-modal LLMs Interpret CT Scans? An Auto-Evaluation Framework for Analyses

Qingqing Zhu, Benjamin Hou, Tejas S. Mathai +7

Automatically interpreting CT scans can ease the workload of radiologists. However, this is challenging mainly due to the scarcity of adequate datasets and reference standards for…

eess.IV2024★ 7 cited

Enhancing chest X-ray datasets with privacy-preserving large language models and multi-type annotations: a data-driven approach for improved classification

Ricardo Bigolin Lanfredi, Pritam Mukherjee, Ronald Summers

In chest X-ray (CXR) image analysis, rule-based systems are usually employed to extract labels from reports for dataset releases. However, there is still room for improvement in la…