Many rare genetic diseases are associated with recognizable craniofacial features. However, traditional approaches for describing facial morphology rely largely on qualitative clinical observation and free-text descriptions, which are often subjective, non-standardized, and difficult to reproduce across observers and i...
Hong-Zhuo Chen, Zhanliang Wang, Florent Pollet et al.· 0 citations
Inference-time aggregation can improve next-generation facial phenotype retrieval without retraining the encoder, supporting a shift from isolated single-image matching toward multi-level aggregation of patient and disorder evidence for rare-disorder prioritization.
Alexander Hustinx, Carolin Kaffiné, Behnam Javanmardi et al.· 0 citations
Results demonstrate that hierarchical modeling of 3D facial geometry enables interpretable, ontology-linked phenotype classification, though performance on rare leaf terms remains limited.
F. Hellmann, Alexander Hustinx, Benjamin D. Solomon et al.· 0 citations
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