ArticleNature genetics2023
PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework.
Article in Nature genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- Early identification of Prader-Willi syndrome in newborns using facial phenotype-based machine learning.Pediatric research · 2026Article
- Beyond the Classics: The Synergy of AI and Genomics Reveals an Expanded Repertoire of Pigmentation Genes.Journal of experimental zoology. Part B, Molecular and developmental evolution · 2026Review
- Machine Learning, Large Language Models, and Multimodal AI for Diagnosing Pediatric Rare Diseases: Scoping Review.Journal of medical Internet research · 2026Article
- Artificial intelligence for pediatric rare disease diagnosis: a multimethod study integrating published evidence and clinician interviews.BMC medical informatics and decision making · 2026Article
- Near-perfect genome sequencing in medical genetics.Nature genetics · 2026Review
- An Adnp frameshift variant disrupts Wnt signalling inducing chromatocytoskeletal defects and autism-related behaviour in male mice.EBioMedicine · 2026Article
- Functional Data Strengthen Clinical Validation of PhenoScore Phenotype-Guided AI for ANKRD11 Missense Variants.Clinical genetics · 2026Article
- Artificial Intelligence in Rare Diseases: Workflow-Integrated Precision Kidney Care.Clinics and practice · 2026Review
- Clusters in craniofacial microsomia and microtia according to facial morphology and craniofacial anomalies.European journal of pediatrics · 2026Article
- ADNP missense variant p.C687R disrupts chromatin regulation and GABAergic differentiation in Helsmoortel-Van der Aa syndrome.Molecular autism · 2026Article
- Inferring genotype-phenotype maps using attention models.PNAS nexus · 2026Article
- De novo variants in KDM2A cause a syndromic neurodevelopmental disorder.American journal of human genetics · 2026Article
- A Systematic Review Illustrates the Expanding Clinical and Molecular Landscape of Helsmoortel-Van der Aa Syndrome.Brain sciences · 2025Review
- Attention-Base deep learning for 3D craniofacial soft tissue landmark detection and diagnosis in orthodontics.Scientific reports · 2025Article
- A frameshift variant in activity-dependent neuroprotective protein (ADNP) causes nucleocytoskeletal alterations in a dizygotic male twin: a case study.Clinical epigenetics · 2025Article
- Recessive genomic and phenotypic variation in consanguineous families with cerebral palsy.medRxiv : the preprint server for health sciences · 2025Article
- SETBP1 variants outside the degron disrupt DNA-binding, transcription and neuronal differentiation capacity to cause a heterogeneous neurodevelopmental disorder.Nature communications · 2025Article
- Current perspectives and challenges of using artificial intelligence in immunodeficiencies.The Journal of allergy and clinical immunology · 2025Review
- Workflow analysis and evaluation of a next-generation phenotyping tool: A qualitative study of Face2Gene.European journal of human genetics : EJHG · 2025Article
- Graph retrieval augmented large language models for facial phenotype associated rare genetic disease.NPJ digital medicine · 2025Article
Corrections and comments
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Authors and funding
33 authors.
Funding
Abstract
Several molecular and phenotypic algorithms exist that establish genotype-phenotype correlations, including facial recognition tools. However, no unified framework that investigates both facial data and other phenotypic data directly from individuals exists. We developed PhenoScore: an open-source, artificial intelligence-based phenomics framework, combining facial recognition technology with Human Phenotype Ontology data analysis to quantify phenotypic similarity. Here we show PhenoScore's ability to recognize distinct phenotypic entities by establishing recognizable phenotypes for 37 of 40 investigated syndromes against clinical features observed in individuals with other neurodevelopmental disorders and show it is an improvement on existing approaches. PhenoScore provides predictions for individuals with variants of unknown significance and enables sophisticated genotype-phenotype studies by testing hypotheses on possible phenotypic (sub)groups. PhenoScore confirmed previously known phenotypic subgroups caused by variants in the same gene for SATB1, SETBP1 and DEAF1 and provides objective clinical evidence for two distinct ADNP-related phenotypes, already established functionally.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.