Major technological breakthroughs in AI systems have the potential to advance biomedicine and benefit healthcare, yet uncertainty exists about their impact and direction of developments. AI systems are being developed for a variety of applications,[1] encompassing ancillary applications, such as the automation of routine administrative tasks, but also applications of significant impact on the provision of quality health services and a patient’s treatment, that could be regulated as medical devices at national level, such as in radiology imaging.

 

 Key AI use cases include:

  • Medical diagnostics: AI systems that can analyse medical images (X-rays, MRIs, CT scans etc.), laboratory testing (genome analysis, slide, imaging) and assess symptoms in order to help identify disease and diagnose health conditions.
  • Predictive analytics: AI systems used to predict patient outcomes, such as risk of disease and potential complications, by data analysis.
  • Personalised medicine: AI systems that help tailor treatment plans to individual patients, optimizing drug therapies and medical interventions by analysing genetic information and other health data.
  • Virtual health assistants: AI-powered chatbots and virtual assistants that provide patient support, including mental health support, by answering questions, scheduling appointments, and offering medication reminders.
  • Remote monitoring and telemedicine: AI-powered wearable devices and telehealth platforms enabling patient monitoring outside of traditional settings.
  • Robotic surgery: AI-powered robotic systems enhancing surgical precision and control.
  • Process management: AI systems used to manage access to treatment, distribute patients within the healthcare system or allocate resources, for example according to urgency or necessity.
  • Medical device development: AI systems used in the design, testing, and optimisation of medical devices.
  • Mental health support: AI tools used for digital therapies, early detection of mental health risks through behavioural data (e.g. digital phenotyping), and personalised mental health interventions including AI-powered chatbots simulating therapeutic interactions.

 

[1] For an overview of AI applications in healthcare, see Report on the Application of Artificial Intelligence in Healthcare and its impact on the “Patient-Doctor” Relationship, Steering Committee for Human Rights in the field of Biomedicine and Health (CDBIO), September 2024, pp. 9-11. See also Ethics and Governance of Artificial Intelligence for Health, World Health Organization, 2021, pp. 6-16.