2026-09-15T07:16:58Zhttps://gredos.usal.es/oai/request

oai:gredos.usal.es:10366/1668072026-02-09T09:53:37Zcom_10366_3948com_10366_3947com_10366_3946com_10366_3823col_10366_3949

Contribution of artificial intelligence to training and diagnosis in medical radiology Juanes Méndez, Juan Antonio Radiology Training and clinical practice Artificial intelligence [EN] Recent advances in deep learning algorithms, the latest technologies in medical image processing and medical training and support systems for radiologists are changing the course of teaching and clinical practice. Through the use and incorporation of artificial intelligence techniques, systems are beginning to be created that are capable of performing tasks that normally require human intelligence, such as image recognition, natural language processing, machine learning and decision making. The integration of these procedures as additional tools in clinical practice requires a validation assessment by the radiological professionals who may use them. Therefore, our aim with this study is to find out the opinion of radiological professionals of different categories and ages, in order to assess whether the incorporation of artificial intelligence in this field is of interest to specialists in radiodiagnosis. 2025-08-26T11:09:08Z 2025-08-26T11:09:08Z 2025-07-14 2099-09-09 info:eu-repo/semantics/article Juanes Méndez, J. A., Izquierdo, M. M., Marcos-Pablos, S., D’Amato, R., & Haro, F. B. (2024, October). Contribution of Artificial Intelligence to Training and Diagnosis in Medical Radiology. In International conference on technological ecosystems for enhancing multiculturality (pp. 221-229). Singapore: Springer Nature Singapore. 2196-4963 2196-4971 http://hdl.handle.net/10366/166807 10.1007/978-981-96-5658-5_22 eng https://doi.org/ 10.1007/978-981-96-5658-5_22 http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/embargoedAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional Springer Science and Business Media Deutschland GmbH