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New AI tools SCANAR and AIDOC accelerate horizon scanning by 65%

Researchers Lena Schmidt and colleagues have developed two open-source Python tools, SCANAR and AIDOC, designed to accelerate the process of horizon scanning, particularly in the healthcare sector. SCANAR automates the retrieval and de-duplication of news articles, while AIDOC utilizes large language models and text embeddings to calculate semantic similarity for relevancy ranking. Initial results indicate that these tools can significantly reduce manual review efforts, with AIDOC showing a theoretical saving of around 65% in manual review at 95% recall. AI

IMPACT These tools could streamline research and innovation tracking across various fields by improving information retrieval and analysis efficiency.

RANK_REASON The item describes a research paper detailing novel tools and their validation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New AI tools SCANAR and AIDOC accelerate horizon scanning by 65%

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The item describes a research paper detailing novel tools and their validation. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Lena Schmidt, Oshin Sharma, Chris Marshall, Sonia Garcia Gonzalez Moral ·

    Horizon Scans can be accelerated using novel information retrieval and artificial intelligence tools

    arXiv:2504.01627v2 Announce Type: replace-cross Abstract: Introduction: Horizon scanning in healthcare assesses early signals of innovation, crucial for timely adoption. Current horizon scanning faces challenges in efficient information retrieval and analysis, especially in grey …