PhD defence E.F. (Eric) Thee

Below is a brief summary of the dissertation:

Age-related macular degeneration is one of the leading causes of irreversible vision loss in older adults. As the population ages, more people will be affected, while eye care services are already under pressure. This thesis investigates how artificial intelligence (AI), large population studies, and molecular data can help move eye care from late detection and treatment towards earlier prediction, prevention, and more personalized care.

Using long-term data from large European studies, including the Rotterdam Study, this thesis shows that subtle changes in the retina can be measured more precisely with AI than with traditional disease categories alone. These measurements can help estimate an individual’s long-term risk of developing advanced macular degeneration, years before severe vision loss occurs. This may allow doctors to monitor high-risk patients more closely and tailor care to the individual patient.

The thesis also shows that the development of age-related macular degeneration is shaped by a combination of genetic susceptibility, metabolism, lifestyle, and general health. This places eye disease in a broader medical context: the retina is not an isolated organ, but part of the body.

Finally, the thesis argues that AI can only improve healthcare if it is evaluated as carefully as any other medical innovation. Epidemiology offers essential tools to assess bias, reliability, generalizability, and real-world value. The broader message is that AI should not make medicine colder or more distant. If used responsibly, it can help medicine become more human again by taking over routine tasks, reducing administrative burden, and giving clinicians more time to listen, build trust, and be fully present for their patients.