37 citations · 76 across the 7 of their papers we have counts for
8 papers
Learning Stability of Replay-Based Co-Optimization for Transmission Expansion under Strategic Bidding
Tomonari Kanazawa, Hikaru Hoshino, Eiko Furutani
This paper investigates the behavior of learning-based co-optimization for transmission expansion under strategic bidding in electricity markets. In this framework, transmission ca…
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…
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…
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,…
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…
A lower prevalence for recessive disorders in a random mating population is a transient phenomenon during and after a growth phase
Luis A. La Rocca, Julia Frank, Heidi Beate Bentzen +4
Despite increasing data from population-wide sequencing studies, the risk for recessive disorders in consanguineous partnerships is still heavily debated. An important aspect that…