Live(r) and Let Live: Combining AI and Citizen Science in Hepatology

Background: The citizen science movement aims to better incorporate citizens in scientific processes. Technology makes it trivial to include citizens for classification, data acquisition, annotation or analysis tasks, thus raising awareness for unknown, yet prevalent diseases such as Metabolic dysfunction-associated steatotic liver disease (MASLD).

Methods: Hepatology inspiring citizen science literature was reviewed, including Galaxy Zoo (astronomy), eteRNA (biology), WOW (meteorology), and Telraam (traffic). Galaxy Zoo showcases the power of citizen based image annotation, leading to better understanding of galaxy formation, whereas eteRNA stimulates gamified problem solving, yielding new and relevant synthesised molecules for scientists. WOW demonstrates how local citizen measurements can produce increased precision for weather model estimates, whereas Telraam empowers citizens to measure traffic intensity, thus influencing policy making.

Results: A “liver zoo” where users annotate lesions, fibrosis and fat deposits on multiple images per patient over time, could enhance disease progression modelling with AI. Like eteRNA, gamification could incentivise nutritional and lifestyle changes, as part of liver patient treatment plans, yielding better health outcomes. A WOW analogy is the encouragement of patients to share nutrition and exercise information, with healthcare providers, allowing doctors to monitor patient progress, adjust treatments and provide feedback. An extension of Telraam is a federated learning approach, where locally trained AI models on data from wearables (thus maintaining privacy) are periodically uploaded to a central server, aggregating them to enhance AI models analysing liver diseases.

Conclusion: Previous findings across multiple disciplines suggest that citizen science can have a major impact on the hepatology community.

Publication History

Article published online:
20 January 2025