Precision medicine aims to tailor healthcare to each person, but trans people are often left out of this research. Little is known about how AI tools in healthcare could be adapted to their specific health needs. This study explored the challenges, obstacles and possible solutions for using AI in personalised medicine for trans people.
The researchers worked together with trans community representatives to co-design the study and its data collection tools, and held three focus groups with 16 trans adults. Participants raised concerns about data privacy, algorithmic bias and the lack of health data that reflects trans experiences. They also worried that AI built on data models that assume everyone is cisgender could lead to misdiagnosis or inappropriate treatment.
At the same time, participants saw opportunities for AI to improve health outcomes. They proposed community-led data collection, more transparent algorithms, including trans-specific health markers in datasets, involving community members in AI development, and ethical frameworks that respect gender diversity. The authors conclude that precision medicine needs a trans-inclusive approach, with AI designed around the health needs and lived realities of trans people.
Learn more about this study here: https://doi.org/10.2196/72325
Reference:
Buslón, N., Cirillo, D., Rios, O., & Perera del Rosario, S. (2025). Exploring gender bias in AI for personalized medicine: Focus group study with trans community members. Journal of Medical Internet Research, 27, e72325.