Radiology
PulseAugur coverage of Radiology — every cluster mentioning Radiology across labs, papers, and developer communities, ranked by signal.
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New CORTEX benchmark aims for trustworthy AI in 3D chest CT analysis
Researchers have introduced CORTEX, a new benchmark designed to improve the trustworthiness of multimodal large language models (MLLMs) in 3D chest CT analysis. Existing datasets often reduce complex radiology reports t…
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AI models exhibit "Inattentional Gap," missing safety signals when tasked
A new research paper introduces the concept of the "Inattentional Gap," describing how language and vision AI models, when conditioned on specific tasks, suppress their ability to report safety-critical signals they wou…
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AI Rewriting of Radiology Reports Creates "Slop Paradox"
A new study published on arXiv examines the impact of AI-driven standardization on radiology reports, revealing a phenomenon termed the "slop paradox." Researchers found that while AI rewriting tasks designed for clinic…
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AI's job impact hinges on task complexity, not just automation
A new analysis suggests that AI's effect on employment is more nuanced than simple automation potential. It highlights that task complexity plays a crucial role, using radiology as an example where AI tools have coexist…
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New architecture links radiology report findings to evidence
Researchers have proposed a new reference architecture for structured radiology reporting that links evidence directly to report content. This human-supervised system aims to extract and organize structured information,…
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MedExpMem enhances VLM diagnostic accuracy with experience memory
Researchers have developed MedExpMem, a novel framework designed to enhance the diagnostic capabilities of vision-language models (VLMs) in medicine. This system allows VLMs to learn from their own diagnostic failures, …
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Doctors face growing AI deepfake crisis, AMA calls for new laws
Doctors are increasingly becoming the subjects of AI-generated deepfake videos used to promote questionable products and spread misinformation, leading to concerns about public trust in the medical field. The American M…
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RadLite fine-tunes small LLMs for CPU-deployable radiology AI
Researchers have developed RadLite, a method for fine-tuning small language models (SLMs) with 3-4 billion parameters for radiology tasks. This approach, utilizing LoRA fine-tuning on models like Qwen2.5-3B-Instruct and…
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@ thomasfuchs @ emilymbender This article is about a study of the use of # LLM # AI in radiology and other medical areas. The study’s conclusions confirm what w
Linguist Emily Bender argues that the current chatbot interface for large language models (LLMs) is not beneficial, despite their utility in tasks like transcription and translation. She criticizes the design choice of …