activity
20222026
most citedImproving Deep Facial Phenotyping for Ultra-rare Disorder Verification Using Model Ensembles

37 citations · 76 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Hierarchical Classification via Cascading Feature Elimination: Application to Human Phenotype Ontology-Aligned Facial Phenotyping (FaceMesh2HPO)

Fabio Hellmann, Alexander Hustinx, Benjamin D. Solomon +4

FaceMesh2HPO is a framework for classifying facial phenotypic descriptors aligned with the Human Phenotype Ontology (HPO) to support clinical diagnosis. Using annotations from 124…

cs.CV2026

Multi-Level Evidence Aggregation for Robust Facial Phenotype Retrieval in Rare Genetic Disorder Prioritization

Alexander Hustinx, Carolin Kaffiné, Behnam Javanmardi +2

AI-assisted facial phenotyping supports rare genetic disorder prioritization by retrieving visually similar diagnosed cases from facial image reference databases such as the Gestal…

q-bio.QM2023★ 4 cited

GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Text

Da Wu, Zhanliang Wang, Hongzhuo Chen +12

Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests, and genetic tests over a prolonged period of time,…

cs.CV2023★ 29 cited

GANonymization: A GAN-based Face Anonymization Framework for Preserving Emotional Expressions

Fabio Hellmann, Silvan Mertes, Mohamed Benouis +5

In recent years, the increasing availability of personal data has raised concerns regarding privacy and security. One of the critical processes to address these concerns is data an…

cs.CV2022★ 37 cited

Improving Deep Facial Phenotyping for Ultra-rare Disorder Verification Using Model Ensembles

Alexander Hustinx, Fabio Hellmann, Ömer Sümer +4

Rare genetic disorders affect more than 6% of the global population. Reaching a diagnosis is challenging because rare disorders are very diverse. Many disorders have recognizable f…

cs.CV2022★ 6 cited

Few-Shot Meta Learning for Recognizing Facial Phenotypes of Genetic Disorders

Ömer Sümer, Fabio Hellmann, Alexander Hustinx +3

Computer vision-based methods have valuable use cases in precision medicine, and recognizing facial phenotypes of genetic disorders is one of them. Many genetic disorders are known…