Publications by authors named "V Yaghmai"

Hepatocellular carcinoma (HCC) is a major global health issue characterized by poor prognosis and complex tumor biology. One of the critical components of the HCC tumor microenvironment (TME) is tumor-associated macrophages (TAMs), which play a pivotal role in modulating tumor growth, immune evasion, and metastasis. Macrophages are divided into two major subtypes: pro-inflammatory M1 and anti-inflammatory M2, both of which may exist in TME with altered function and proportion.

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Background: Multidose iodinated contrast media (ICM) injectors have shown promise in reducing ICM waste. This study aims to evaluate the impact of patient volume on ICM waste reduction in multidose injectors.

Methods: CT studies performed over one-year period with a multidose injector at our emergency CT unit.

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Prostate-Specific Membrane Antigen (PSMA) positron emission tomography (PET) / computed tomography (CT) has become essential in managing prostate cancer, offering superior diagnostic accuracy. The introduction of the U.S.

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The Radiology Research Alliance (RRA) of the Association of Academic Radiology (AAR) creates task forces to study emerging trends shaping the future of radiology. This article highlights the findings of the AAR-RRA Task Force on Balancing High Clinical Volumes and non-relative value unit (Non-RVU)-Generating Activities. The Task Force's mission was to evaluate and emphasize the value of non-RVU-generating activities that academic radiologists perform.

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Article Synopsis
  • The study explores how well contemporary large language models (LLMs) can analyze radiology board-style questions that include images, testing their multimodal capabilities.
  • Researchers evaluated 280 selected questions using three formats (multimodal, image-only, text-only) with three LLMs: GPT-4V, Gemini 1.5 Pro, and Claude 3.5 Sonnet, applying statistical tests to analyze their performance.
  • Results showed that while GPT-4V and Gemini performed similarly across different input types, Claude 3.5 Sonnet excelled with text and multimodal inputs, but underperformed with image-only inputs, indicating the limitations of LLMs in utilizing images for improved performance in radiology contexts
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