Understand
Foundations, health examples and criteria for assessing value and risk.
Specialist programme · Custom design
Generative AI in Cardiology
Artificial intelligence applied to cardiovascular practice, research and clinical communication.
8 specialist modules60% learning · 40% labsCustom final project
Overview
Cardiology with Generative AI
A pathway for integrating AI into evidence, risk stratification, follow-up and cardiovascular decision-making.
The proposal combines foundations, applied work and a final project focused on the specialty's priorities.
Objectives
Understand, experiment and implement
Technology is approached through professional judgement: where it creates value, where it does not, and how to use it safely.
- Interpret the capabilities and limits of AI in cardiovascular care.
- Accelerate evidence review and preparation of clinical sessions.
- Explore multimodal AI in tests, imaging and longitudinal data.
- Design safe support for follow-up and decision-making.
- Improve risk communication and patient education.
Content
Eight modules connected to practice
A shared AI core and a clinical strand built around each professional community's priorities.
01Generative AI foundations
Language models, prompting, reasoning, limitations, bias and first applications in cardiology.
02Evidence and scientific research
Search, synthesis and critical reading of cardiovascular evidence with citations and traceability.
03Clinical documentation and knowledge
Clinical sessions, reports, guidelines, protocols and educational material with professional review.
04Risk, imaging and cardiovascular decisions
Risk stratification, tests, ECG and imaging as multimodal sources.
05Multimodality and health data
Text, images, audio, video and structured data: opportunities, evaluation and limits.
06Agents and specialist assistants
Assistants for research, documentation, education and workflow coordination.
07Integration in cardiology
A workflow applied to prevention, diagnosis, treatment or follow-up.
08Ethics, regulation and implementation
Privacy, safety, bias, accountability and governance for defensible implementation.
Methodology
Learning by doing, through a real challenge
Each cohort combines practical seminars, labs, peer learning and support around an implementation project.
Experiment
Labs using current tools and specialty-specific cases.
Implement
A final project based on a real cardiology challenge.
Participant profile
For the cardiovascular community
No programming is required. Professional expertise and the willingness to innovate responsibly are the starting point.
Cardiology specialists
Professionals involved in prevention, diagnosis, treatment, rehabilitation and follow-up.
Research and management
Researchers, nursing and roles linked to imaging, data, quality and innovation.
Starting knowledge
Basic research methodology and general familiarity with digital tools. No technical background is required.
Faculty
Technology, innovation and clinical judgement
The N Company team is led by programme director Consuelo Verdú, includes Dr Javier Mendoza as medical advisor and welcomes specialist guest faculty for each therapeutic area.
Néstor Guerra
Corporate innovation, artificial intelligence and organisational adoption. Engineer and Executive MBA.
nestor@ncompany.es
Consuelo Verdú
Programme director. Innovation, creativity and transformation. Economist, ESADE MBA and educator.
consuelo@ncompany.es
Javier Fuentes
Technology, artificial intelligence and entrepreneurship. University lecturer and mentor.
javier@ncompany.es
Javier Mendoza, MD, PhD
Medical advisor. Gastroenterologist with expertise in digital health, endoscopy and AI in clinical practice.
LinkedInGenerative AI in Cardiology
Request informationLet us design a cohort for your society
We tailor cases, schedule, tools and the final project to the cardiovascular community.