Litcius/Paper detail

How does artificial intelligence master urological board examinations? A comparative analysis of different Large Language Models’ accuracy and reliability in the 2022 In-Service Assessment of the European Board of Urology

Lisa Kollitsch, Klaus Eredics, Martin Marszalek, Michael Rauchenwald, Sabine Brookman‐May, Maximilian Burger, Katharina Körner-Riffard, Matthias May

2024World Journal of Urology31 citationsDOI

Topics & Concepts

MedicineNephrologyReliability (semiconductor)UrologyInternal medicineMedical physicsGynecologyPower (physics)Quantum mechanicsPhysicsArtificial Intelligence in Healthcare and EducationMedical Malpractice and Liability IssuesClinical Reasoning and Diagnostic Skills
How does artificial intelligence master urological board examinations? A comparative analysis of different Large Language Models’ accuracy and reliability in the 2022 In-Service Assessment of the European Board of Urology | Litcius