37 citations · 74 across the 6 of their papers we have counts for
6 papers
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…
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data
Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle +35
Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Publ…
Towards Automated COVID-19 Presence and Severity Classification
Dominik Müller, Niklas Schröter, Silvan Mertes +6
COVID-19 presence classification and severity prediction via (3D) thorax computed tomography scans have become important tasks in recent times. Especially for capacity planning of…
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…
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…
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…