Jaana Auvinen, Tarja Suominen, Helena Leino-Kilpi, Klaus Helkama
The development of moral judgment during nursing education in Finland
Nurse education today
large language models subset artificial intelligence immense potential support human tasks role models science medicine unclear requiring strong critical thinking analysis skills objective study evaluate gpt4s abilities assess postoperative complications renal surgeries discharge summaries compiled patient information deidentified pythonbased program prompts engineered gpt4 assess presence postoperative complications gpt4 asked interpret complications claviendindo classification institutionalspecific category gpt4s database compared humancurated database discrepancies manually reviewed calculate match accuracy rates approximately 944 renal surgeries conducted august 2005 march 2022 796 match rate gpt4 humancurated data detecting postoperative complications accuracy rates 867 gpt4 929 humancurated subgroup 139 patients complication detected gpt4 human available claviendindo classification category information 374 overall match rate claviendindo grade 554 match rate category gpt4 able accurately detect postoperative complications struggled complex task analyzing complications especially claviendindo classification requires critical thinking interpretation gpt4 yet ready advanced postoperative complication analysis still used support clinicians endeavor