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LLMs used to analyze blood pressure variations by sex from literature

By PulseAugur Editorial · [1 sources] ·

Researchers have explored the use of Large Language Models (LLMs) to analyze blood pressure variations across biological sexes from scientific literature. The study utilized NLP techniques and an Apache Solr-based search engine to retrieve relevant articles from PubMed. Experiments with few-shot learning and zero-shot LLMs like Llama 3 and GPT-3.5 were conducted to extract mean and standard deviation of blood pressure values, along with associated biological sex indicators. AI

IMPACT This research demonstrates LLMs' potential in extracting nuanced biological data from scientific literature, potentially improving health research.

RANK_REASON The item is an academic paper detailing research methodology and findings. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLMs used to analyze blood pressure variations by sex from literature

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The item is an academic paper detailing research methodology and findings. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yuting Guo, Seyedeh Somayyeh Mousavi, Reza Sameni, Abeed Sarker ·

    Leveraging Few-Shot Learning and Large Language Models for Analyzing Blood Pressure Variations Across Biological Sex from Scientific Literature

    arXiv:2402.01826v2 Announce Type: replace-cross Abstract: Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often without adjusting BP readings for individual demographic factors such as sex an…

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