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AI for Healthcare Research & Education

Creator: Rayne Zaayman-Gallant / EMBL. Copyright: CC-BY-NC-ND 4.0 Copyright: © European Molecular Biology Laboratory (EMBL)

This guide is intended to provide guidance on the current best practices of using Generative Artificial Intelligence (GenAI) applications for healthcare research and education.

About Generative AI

What is GenAI?

GenAI is a division of AI where new content is created based on the inputs (prompts) they receive via learning algorithms that make predictions. The output can be in the form of text, images, audio, video, code and more.

How GenAI can assist clinicians, researchers, and learners

With guidance and education, GenAI applications can enhance patient care and research workflow by locating clinical evidence in a timely manner, streamlining tasks, and accelerating writing and data analysis in publications. AI systems are designed to augment and support healthcare professionals, freeing up their time to focus on more complex and critical tasks and more meaningful interactions.

Implications of using GenAI

Some of the risks of using GenAI applications include but are not limited to: 

  • Hallucinations or fabrications, inaccurate or non existent information
  • Bias, privacy, copyright
  • Ethical and legal challenges, including accountability, liability, and consent
  • Misuse
  • Environmental Impact
  • Lack of transparency

Detailed information on the implications of GenAI applications is available on our Ethical & Legal Considerations page.