ChatGPT-4.0: A Promising Tool for Diagnosing Thyroid Nodules DOI Creative Commons
Guorong Lyu, Daorong Hong, Chunyan Huang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: June 26, 2024

Abstract Objective This study aims to explore the application value of ChatGPT-4.0 in ultrasonic image analysis thyroid nodules, comparing its diagnostic efficacy and consistency with that sonographers. Methods is a prospective based on real clinical scenarios. The included 124 patients nodules confirmed by pathology who underwent ultrasound examinations at Fujian Medical University Affiliated Second Hospital. A physician not involved collected images capturing three for each nodule—the maximum cross-sectional, longitudinal, section best representing nodular characteristics—for analysis, classified according 2020 China Thyroid Nodule Malignancy Risk Stratification Guide (C-TIRADS). Two sonographers different qualifications (a resident an attending physician) independently performed examinations, also classifying C-TIRADS guidelines. Using fine needle aspiration (FNA) biopsy or surgical results as gold standard, were compared those Results (1) diagnosed sensitivity 86.2%, specificity 60.0%, AUC 0.731, comparable resident's 85.1%, 66.7%, 0.759 (p > 0.05), but lower than physician's 97.9% 0.889 < 0.05). (2) showed good nodule classification (Kappa = 0.729), pathological diagnosis was between values 0.457 vs 0.816 respectively). Conclusion has certain risk stratification level physicians.

Language: Английский

Cutting Edge to Cutting Time: Can ChatGPT Improve the Radiologist’s Reporting? DOI
Rayan A. Ahyad,

Yasir Zaylaee,

Tasneem Hassan

et al.

Deleted Journal, Journal Year: 2024, Volume and Issue: unknown

Published: July 17, 2024

Radiology-structured reports (SR) have many advantages over free text (FT), but the wide implementation of SR is still lagging. A powerful tool such as GPT-4 can address this issue. We aim to employ a web-based reporting powered by capable converting FT and then evaluate its impact on time report quality. Thirty abdominopelvic CT scans were reported two radiologists across sessions (15 each): control session using traditional methods an AI-assisted employing GPT-4-powered web application structure into structured reports. For each radiologist, output included 15 finalized reports, pre-edits, post-edit Reporting turnaround times assessed, including total (TRT) case (TATc). Quality assessments conducted blinded radiologists. TRT TATc decreased with use tool, although statistically not significant (p-value > 0.05). Mean for RAD-1 from 00:20:08 00:16:30 (hours:minutes:seconds) 05:02:00 04:08:00. RAD-2 00:12:04 00:10:04 03:01:00 02:31:00. scores without AI-assistance comparable no differences. Adjusting removing editing showed results compared both < The generate while reducing sacrificing Editing potential area further improvement.

Language: Английский

Citations

2
Assessing the reliability of ChatGPT4 in the appropriateness of radiology referrals DOI Creative Commons
Marco Parillo, Federica Vaccarino, Daniele Vertulli

et al.

The Royal College of Radiologists Open, Journal Year: 2024, Volume and Issue: 2, P. 100155 - 100155

Published: Jan. 1, 2024

Language: Английский

Citations

2
ChatGPT-4.0: A Promising Tool for Diagnosing Thyroid Nodules DOI Creative Commons
Guorong Lyu, Daorong Hong, Chunyan Huang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: June 26, 2024

Abstract Objective This study aims to explore the application value of ChatGPT-4.0 in ultrasonic image analysis thyroid nodules, comparing its diagnostic efficacy and consistency with that sonographers. Methods is a prospective based on real clinical scenarios. The included 124 patients nodules confirmed by pathology who underwent ultrasound examinations at Fujian Medical University Affiliated Second Hospital. A physician not involved collected images capturing three for each nodule—the maximum cross-sectional, longitudinal, section best representing nodular characteristics—for analysis, classified according 2020 China Thyroid Nodule Malignancy Risk Stratification Guide (C-TIRADS). Two sonographers different qualifications (a resident an attending physician) independently performed examinations, also classifying C-TIRADS guidelines. Using fine needle aspiration (FNA) biopsy or surgical results as gold standard, were compared those Results (1) diagnosed sensitivity 86.2%, specificity 60.0%, AUC 0.731, comparable resident's 85.1%, 66.7%, 0.759 (p > 0.05), but lower than physician's 97.9% 0.889 < 0.05). (2) showed good nodule classification (Kappa = 0.729), pathological diagnosis was between values 0.457 vs 0.816 respectively). Conclusion has certain risk stratification level physicians.

Language: Английский

Citations

0