Developing AI for specialized medical diagnostics has unique challenges, especially when working with limited datasets. Our journey in gynecological AI reveals the critical importance of problem reframing and iterative development. By systematically addressing data scarcity and refining our approach, we transformed initial setbacks into a robust diagnostic tool. This case study showcases how creative technical solutions can overcome data limitations, offering insights for AI practitioners working in niche, data-constrained domains.

Rosilari Bellacosa co-founded SynDiag in 2018 and is currently serving as CTO. SynDiag uses AI to help doctors diagnose gynecological pathologies early. Her mission at Syndiag is to build tools that empower doctors and patients.