Luordo, DavideTorres Arrese, MartaTristan Calvo, CristinaShani Shani, Kirti DayalRodríguez Cruz, Luis MiguelGarcía Sánchez, Francisco JavierLagares Gómez-Abascal, AlfonsoRubio García, RafaelDelgado Jiménez, Juan FranciscoPérez Carreras, MercedesDíez Lobato, RamiroGranizo Martinez, Juan JoséTung-Chen, YaleVillena Garrido, María Victoria2025-07-072025-07-072025-01-23Luordo, D., Torres Arrese, M., Tristán Calvo, C., Shani Shani, K. D., Rodríguez Cruz, L. M., García Sánchez, F. J., Lagares Gómez-Abascal, A., Rubio García, R., Delgado Jiménez, J., Pérez Carreras, M., Diez Lobato, R., Granizo Martínez, J. J., Tung-Chen, Y., & Villena Garrido, M. V. (2025). Application of Artificial Intelligence as an Aid for the Correction of the Objective Structured Clinical Examination (OSCE). Applied Sciences, 15(3), 1153. https://doi.org/10.3390/app150311532076-341710.3390/app15031153https://hdl.handle.net/20.500.14352/122244The assessment of clinical competencies is essential in medical training, and the Objective Structured Clinical Examination (OSCE) is an essential tool in this process. There are multiple studies exploring the usefulness of artificial intelligence (AI) in medical education. This study explored the use of the GPT-4 AI model to grade clinical reports written by students during the OSCE at the Teaching Unit of the 12 de Octubre and Infanta Cristina University Hospitals, part of the Faculty of Medicine at the Complutense University of Madrid, comparing its results with those of human graders. Ninety-six (96) students participated, and their reports were evaluated by two experts, an inexperienced grader, and the AI using a checklist designed during the OSCE planning by the teaching team. The results show a significant correlation between the AI and human graders (ICC = 0.77 for single measures and 0.91 for average measures). AI was more stringent, assigning scores on an average of 3.51 points lower (t = −15.358, p < 0.001); its correction was considerably faster, completing the analysis in only 24 min compared to the 2–4 h required by human graders. These results suggest that AI could be a promising tool to enhance efficiency and objectivity in OSCE grading.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/journal articlehttps://doi.org/10.3390/app15031153https://www.mdpi.com/2076-3417/15/3/1153open access616.1/.9004.8artificial intelligenceobjective structured clinical examination (OSCE)medical educationclinical competency assessmentAI in healthcareAI-assisted gradinghuman–AI comparison in gradingdigital OSCE evaluationmedical report evaluationMedicina interna3314.99 Otras