PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 24, 2026Insights into Imaging1 citationsOpen Access

Comparative evaluation of large language models for generating CAD-RADS 2.0-compliant diagnostic conclusions in cardiac CT reports

GLGiovanni LorussoGRGiorgio RuscinoASAlessia Spitaleri

Key Points

  • This research aims to assess the effectiveness of large language models in generating CAD-RADS 2.0-compliant diagnostic conclusions for cardiac CT reports.
  • Comparison of various large language models in generating reports
  • Evaluation of compliance with CAD-RADS 2.0 standards
  • Assessment of reporting efficiency
  • LLMs showed strong potential for automating structured reporting
  • Significant improvements in reporting efficiency were observed
  • Further optimization of LLMs is necessary before they can be integrated clinically

Abstract

LLMs demonstrated strong potential in automating CAD-RADS 2.0-compliant structured reporting for CCTA. LLMs could significantly enhance efficiency in radiological reporting. LLMs need further optimization before clinical integration.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Lorusso et al. (2026) studied this question.

synapsesocial.com/papers/69eb08ef553a5433e34b3a15https://doi.org/10.1186/s13244-026-02285-6
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Tailoring Large Language Models to Radiology: A Preliminary Approach to LLM Adaptation for a Highly Specialized Domain2023 · 40 citations
  2. 2Coronary Computed Tomography Angiography From Clinical Uses to Emerging Technologies2020 · 300 citations
  3. 3Chatbots and Large Language Models in Radiology: A Practical Primer for Clinical and Research Applications2024 · 327 citations
  4. 4Artificial intelligence for detection and characterization of focal hepatic lesions: a review2024 · 7 citations
  5. 5Large language models for structured reporting in radiology: performance of GPT-4, ChatGPT-3.5, Perplexity and Bing2023 · 86 citations