The Integration of Artificial Intelligence in Undergraduate Medical Education in Spain: Descriptive Analysis and International Perspectives

• URL: http://arxiv.org/abs/2510.17938v1
• Date: Mon, 20 Oct 2025 16:22:54 GMT
• Title: The Integration of Artificial Intelligence in Undergraduate Medical Education in Spain: Descriptive Analysis and International Perspectives
• Authors: Ana Enériz Janeiro, Karina Pitombeira Pereira, Julio Mayol, Javier Crespo, Fernando Carballo, Juan B. Cabello, Manel Ramos-Casals, Bibiana Pérez Corbacho, Juan Turnes,
• Abstract summary: AI is transforming medical practice and redefining the competencies that future healthcare professionals need to master.<n>The University of Ja'en is the only institution offering a compulsory course with AI content.<n>The integration of AI into the medical degree in Spain is incipient, fragmented, and uneven, with a low weight in Andalusia.
• Score: 31.458406135473805
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: AI is transforming medical practice and redefining the competencies that future healthcare professionals need to master. Despite international recommendations, the integration of AI into Medicine curricula in Spain had not been systematically evaluated until now. A cross-sectional study (July-September 2025) including Spanish universities offering the official degree in Medicine, according to the 'Register of Universities, Centers and Degrees (Registro de Universidades, Centros y T\'itulos RUCT)'. Curricula and publicly available institutional documentation were reviewed to identify courses and competencies related to AI in the 2025-2026 academic year. The analysis was performed using descriptive statistics. Of the 52 universities analyzed, ten (19.2%) offer specific AI courses, whereas 36 (69.2%) include no related content. Most of the identified courses are elective, with a credit load ranging from three to six ECTS, representing on average 1.17% of the total 360 credits of the degree. The University of Ja\'en is the only institution offering a compulsory course with AI content. The territorial analysis reveals marked disparities: Andalusia leads with 55.5% of its universities incorporating AI training, while several communities lack any initiative in this area. The integration of AI into the medical degree in Spain is incipient, fragmented, and uneven, with a low weight in ECTS. The limited training load and predominance of elective courses restrict the preparation of future physicians to practice in a healthcare environment increasingly mediated by AI. The findings support the establishment of minimum standards and national monitoring of indicators.

Related papers

• AI-PACE: A Framework for Integrating AI into Medical Education [5.649637602119857]
  The integration of artificial intelligence into healthcare is accelerating, yet medical education has not kept pace with these technological advancements.<n>This paper synthesizes current knowledge on AI in medical education through a comprehensive analysis of the literature.<n>The aim is highlighting the critical need for structured AI education across the medical learning continuum.
  arXiv  Detail & Related papers  (2026-02-11T04:52:26Z)
• Artificial Intelligence in Spanish Gastroenterology: high expectations, limited integration. A national survey [32.505127447635864]
  Artificial intelligence (AI) has emerged as a disruptive innovation in medicine, yet its adoption within gastroenterology remains limited and poorly characterized.<n>We aimed to examine knowledge, practical applications, perceived barriers, and expectations regarding AI among gastroenterology specialists in Spain.
  arXiv  Detail & Related papers  (2026-01-14T16:58:53Z)
• Artificial Intelligence for All? Brazilian Teachers on Ethics, Equity, and the Everyday Challenges of AI in Education [0.0]
  This study examines the perceptions of Brazilian K-12 education teachers regarding the use of AI in education, specifically General Purpose AI.<n>The study shows that Brazil is still in a bottom-up model for AI integration, missing official curricula to guide its implementation and structured training for teachers and students.
  arXiv  Detail & Related papers  (2025-12-29T19:58:09Z)
• A Large-Scale Vision-Language Dataset Derived from Open Scientific Literature to Advance Biomedical Generalist AI [70.06771291117965]
  We introduce Biomedica, an open-source dataset derived from the PubMed Central Open Access subset.<n>Biomedica contains over 6 million scientific articles and 24 million image-text pairs.<n>We provide scalable streaming and search APIs through a web server, facilitating seamless integration with AI systems.
  arXiv  Detail & Related papers  (2025-03-26T05:56:46Z)
• Data-Driven Analysis of AI in Medical Device Software in China: Deep Learning and General AI Trends Based on Regulatory Data [3.1485639585141114]
  We leverage a data-driven approach to automatically extract and analyze AI-enabled medical devices.<n>More than 4 million entries were assessed, identifying 2,174 MDSW registrations.<n>Leading medical specialties utilizing AIMD include respiratory (20.5%), ophthalmology/endocrinology (12.8%), and orthopedics (10.3%)
  arXiv  Detail & Related papers  (2024-11-11T21:28:50Z)
• AI in radiological imaging of soft-tissue and bone tumours: a systematic review evaluating against CLAIM and FUTURE-AI guidelines [1.5332408886895255]
  Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with variable clinical behaviours and treatment approaches.<n>This systematic review provides an overview of Artificial Intelligence (AI) methods using radiological imaging for diagnosis and prognosis of these tumours.
  arXiv  Detail & Related papers  (2024-08-22T15:31:48Z)
• Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants [176.39275404745098]
  We evaluate whether two AI assistants, GPT-3.5 and GPT-4, can adequately answer assessment questions.<n>GPT-4 answers an average of 65.8% of questions correctly, and can even produce the correct answer across at least one prompting strategy for 85.1% of questions.<n>Our results call for revising program-level assessment design in higher education in light of advances in generative AI.
  arXiv  Detail & Related papers  (2024-08-07T12:11:49Z)
• Promoting AI Competencies for Medical Students: A Scoping Review on Frameworks, Programs, and Tools [1.8402287369342527]
  Despite the evolving importance of AI in healthcare, the extent to which it has been adopted into traditional and often-overloaded medical curricula is unknown. This review provides a road map for developing practical and relevant education strategies for building an AI-competent healthcare workforce.
  arXiv  Detail & Related papers  (2024-07-10T16:34:41Z)
• FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare [73.78776682247187]
  Concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare.
  arXiv  Detail & Related papers  (2023-08-11T10:49:05Z)
• Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021 [73.06361680847708]
  In 1960 14% of 333 research fields were related to AI, but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.
  arXiv  Detail & Related papers  (2023-06-15T14:08:07Z)
• Large Language Models Leverage External Knowledge to Extend Clinical Insight Beyond Language Boundaries [48.48630043740588]
  Large Language Models (LLMs) such as ChatGPT and Med-PaLM have excelled in various medical question-answering tasks. We develop a novel in-context learning framework to enhance their performance.
  arXiv  Detail & Related papers  (2023-05-17T12:31:26Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.