mlsanityData to 14 Oct 2026

PRECISE Framework: GPT-based Text For Improved Readability, Reliability, and Understandability of Radiology Reports For Patient-Centered Care

arXiv 2403.00788 ↗First posted 20 Feb 2024cs.CL cs.AI cs.HCcited by 0

Not on the map. Why?

Abstract (arXiv)

This study introduces and evaluates the PRECISE framework, utilizing OpenAI's GPT-4 to enhance patient engagement by providing clearer and more accessible chest X-ray reports at a sixth-grade reading level. The framework was tested on 500 reports, demonstrating significant improvements in readability, reliability, and understandability. Statistical analyses confirmed the effectiveness of the PRECISE approach, highlighting its potential to foster patient-centric care delivery in healthcare decision-making.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 42 references that are in the map. First posted on arXiv 20 Feb 2024.

Builds on

3 of 42 references.

References · 3

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,234
  3. 2023Gpt-4: A Review on Advancements and Opportunities in Natural Language Processingcited by 15

Built on by

Not cited yet.