AI‐driven simplification of surgical reports in gynecologic oncology: A potential tool for patient education DOI Creative Commons
M Riedel, Bastian Meyer,

R.D. Rubens

et al.

Acta Obstetricia Et Gynecologica Scandinavica, Journal Year: 2025, Volume and Issue: unknown

Published: May 14, 2025

Abstract Introduction The emergence of large language models heralds a new chapter in natural processing, with immense potential for improving medical care and especially oncology. One recent publicly available example is Generative Pretraining Transformer 4 (GPT‐4). Our objective was to evaluate its ability rephrase original surgical reports into simplified versions that are more comprehensible patients. Specifically, we aimed investigate discuss the potential, limitations, associated risks using these patient education information gynecologic Material Methods We tasked GPT‐4 generating from n = 20 reports. Patients were provided both their report corresponding version generated by GPT‐4. Alongside reports, patients received questionnaires designed facilitate comparative assessment between Furthermore, clinical experts evaluated artificial intelligence (AI)‐generated regard accuracy quality. Results significantly improved our patients' understanding, particularly procedure, outcome, risks. However, despite being accessible relevant, highlighted concerns about lack precision. Conclusions Advanced like can transform unedited improve clarity procedure outcomes. It offers considerable promise enhancing education. precision underscore need rigorous oversight safely integrate AI Over medium term, AI‐generated, reports—and other records—could be effortlessly integrated standard automated postoperative digital discharge systems.

Language: Английский

A Comparative Study on the Question-Answering Proficiency of Artificial Intelligence Models in Bladder-Related Conditions: An Evaluation of Gemini and ChatGPT 4.o DOI Open Access
Mustafa Azizoğlu, Sergey Klyuev

Medical Records, Journal Year: 2025, Volume and Issue: 7(1), P. 201 - 205

Published: Jan. 10, 2025

Aim: The rapid evolution of artificial intelligence (AI) has revolutionized medicine, with tools like ChatGPT and Google Gemini enhancing clinical decision-making. ChatGPT's advancements, particularly GPT-4, show promise in diagnostics education. However, variability accuracy limitations complex scenarios emphasize the need for further evaluation these models medical applications. This study aimed to assess agreement between 4.o AI identifying bladder-related conditions, including neurogenic bladder, vesicoureteral reflux (VUR), posterior urethral valve (PUV). Material Method: study, conducted October 2024, compared AI's on 51 questions about VUR, PUV. Questions, randomly selected from pediatric surgery urology materials, were evaluated using metrics statistical analysis, highlighting models' performance agreement. Results: demonstrated similar across PUV questions, true response rates 66.7% 68.6%, respectively, no statistically significant differences (p>0.05). Combined all topics was 67.6%. Strong inter-rater reliability (κ=0.87) highlights their Conclusion: comparable ChatGPT-4.o key performance.

Language: Английский

Citations

0
AI‐driven simplification of surgical reports in gynecologic oncology: A potential tool for patient education DOI Creative Commons
M Riedel, Bastian Meyer,

R.D. Rubens

et al.

Acta Obstetricia Et Gynecologica Scandinavica, Journal Year: 2025, Volume and Issue: unknown

Published: May 14, 2025

Abstract Introduction The emergence of large language models heralds a new chapter in natural processing, with immense potential for improving medical care and especially oncology. One recent publicly available example is Generative Pretraining Transformer 4 (GPT‐4). Our objective was to evaluate its ability rephrase original surgical reports into simplified versions that are more comprehensible patients. Specifically, we aimed investigate discuss the potential, limitations, associated risks using these patient education information gynecologic Material Methods We tasked GPT‐4 generating from n = 20 reports. Patients were provided both their report corresponding version generated by GPT‐4. Alongside reports, patients received questionnaires designed facilitate comparative assessment between Furthermore, clinical experts evaluated artificial intelligence (AI)‐generated regard accuracy quality. Results significantly improved our patients' understanding, particularly procedure, outcome, risks. However, despite being accessible relevant, highlighted concerns about lack precision. Conclusions Advanced like can transform unedited improve clarity procedure outcomes. It offers considerable promise enhancing education. precision underscore need rigorous oversight safely integrate AI Over medium term, AI‐generated, reports—and other records—could be effortlessly integrated standard automated postoperative digital discharge systems.

Language: Английский

Citations

0