The Rare Lens: AI-based image recognition for rare disease diagnoses

The Rare Lens: AI-based image recognition for rare disease diagnoses There are around 6000 rare diseases, which affect over 300 million people worldwide. Rare diseases are often difficult to diagnose, and people affected by a rare disease wait an average of five years or more for a correct diagnosis, which can be a heavy burden on patients and also hinders rare disease research and drug development. Artificial Intelligence (AI) can help address these diagnostic challenges. One promising approach is Next-Generation Phenotyping (NGP), which uses AI to detect disease-specific phenotypic patterns – such as distinct facial features – commonly associated with rare diseases, to support diagnosis and guide genetic testing. In the newest episode of the BioRevolution podcast, Andreas Horchler and Louise von Stechow spoke to two researchers from the University of Bonn working on next-generation phenotyping approaches: Dr. Adele Ruder, MSL for GestaltMatcher, and Dr. Behnam Javanmardi, Group Leader: AI for Rare Diseases and Head of Bone2Gene. We explored the potential of AI-driven diagnosis for rare diseases and what this could mean for people affected by rare diseases, their physicians, and researchers and drug developers in the rare disease space. Find Adele and GestaltMatcher here: https://www.linkedin.com/in/adeleruder/ https://www.gestaltmatcher.org/ Find Behnam and Bone2Gene here: https://www.linkedin.com/in/behnam-javanmardi/ https://bone2gene.org For further reading explore the following references: 1. https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(24)00056-1/fulltext https://www.nature.com/articles/s41431-024-01604-z 2. https://pubmed.ncbi.nlm.nih.gov/19627523/ 3. https://www.researchsquare.com/article/rs-2110140/v1 4. https://elifesciences.org/articles/02020 5. https://www.face2gene.com/ 6. https://facematch.org.au/home 7. https://cliniface.org/ 8. https://www.gestaltmatcher.org/ 9. https://bone2gene.org/ 10. https://www.nature.com/articles/s41591-018-0279-0 11. https://www.nature.com/articles/s10038-019-0619-z 12. https://www.nature.com/articles/s41588-021-01010-x 13. https://ieeexplore.ieee.org/document/10030218 14. https://www.nature.com/articles/s41431-025-01787-z https://doi.org/10.1007/s00112-024-02118-0 15. https://pubmed.ncbi.nlm.nih.gov/36779427/ 16. https://www.nature.com/articles/s41588-023-01469-w 17. https://www.medrxiv.org/content/10.1101/2023.06.06.23290887v4 18. https://www.nature.com/articles/s41599-024-02894-w 19. https://www.nature.com/articles/d41586-022-03050-7 20. https://www.nature.com/articles/s41746-024-01232-3 21. https://advanced.onlinelibrary.wiley.com/doi/10.1002/advs.202414507 22. https://www.medrxiv.org/content/10.1101/2023.06.06.23290887v4.full.pdf Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow