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Integrative analysis of transcriptome dynamics during human craniofacial development identifies candidate disease genes

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Expanding the phenotypic spectrum of NAA10-related neurodevelopmental syndrome and NAA15-related neurodevelopmental syndrome

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Deeplasia: deep learning for bone age assessment validated on skeletal dysplasias

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Spliceosome Malfunction Causes Neurodevelopmental Disorders with Overlapping Features

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PSMC3 proteasome subunit variants are associated with neurodevelopmental delay and type I interferon production

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Role of CAMK2D in neurodevelopment and associated conditions

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

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Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases

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Applying artificial intelligence to rare diseases: a literature review highlighting lessons from Fabry disease

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Next-generation phenotyping of inherited retinal diseases from multimodal imaging with Eye2Gene

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Rare diseases of epigenetic origin: Challenges and opportunities

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A novel syndrome associated with prenatal fentanyl exposure

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Artificial intelligence-powered nanomedicine

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KBG syndrome: videoconferencing and use of artificial intelligence driven facial phenotyping in 25 new patients

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Neural Networks for Classification and Image Generation of Aging in Genetic Syndromes

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Democratising or disrupting diagnosis? Ethical issues raised by the use of AI tools for rare disease diagnosis

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GestaltMatcher Database - A global reference for facial phenotypic variability in rare human diseasesPreprint

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Perspectives on the future of dysmorphology

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Multimodal analysis methods in predictive biomedicine

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Recognition of Genetic Conditions After Learning With Images Created Using Generative Artificial Intelligence

Waikel, R. L., Othman, A. A., Patel, T., Hanchard, S. E. L., Hu, P., Tekendo‐Ngongang, C., Duong, D., & Solomon, B. D. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.2609 · Cited by 26 · see citing works

Prediagnosis recognition of acute ischemic stroke by artificial intelligence from facial images

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Delineation of the adult phenotype of Coffin–Siris syndrome in 35 individuals

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BCL11A intellectual developmental disorder: defining the clinical spectrum and genotype-phenotype correlations

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PHIP-associated Chung-Jansen syndrome: Report of 23 new individuals

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The neurodevelopmental and facial phenotype in individuals with a TRIP12 variant

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Population-specific facial traits and diagnosis accuracy of genetic and rare diseases in an admixed Colombian population

Echeverry, L. M., Candelo, E., Gomez-Pineda, E., Solís, P., Ramírez, D., Ortiz, D., González, A., Sevillano, X., Cuéllar, J. C., Pachajoa, H., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-33374-x · Cited by 22 · see citing works

De novo variants of CSNK2B cause a new intellectual disability-craniodigital syndrome by disrupting the canonical Wnt signaling pathway

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Addressing diagnostic gaps and priorities of the global rare diseases community: Recommendations from the IRDiRC diagnostics scientific committee

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Graph retrieval augmented large language models for facial phenotype associated rare genetic disease

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Validation of 3 Computer-Aided Facial Phenotyping Tools (DeepGestalt, GestaltMatcher, and D-Score): Comparative Diagnostic Accuracy Study

Reiter, A. M. V., Pantel, J. T., Danyel, M., Horn, D., Ott, C., & Mensah, M. A. (2024) · Journal of Medical Internet Research · doi:10.2196/42904 · Cited by 19 · see citing works

Biallelic variants in CRIPT cause a Rothmund-Thomson-like syndrome with increased cellular senescence

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Application of the Face2Gene tool in an Italian dysmorphological pediatric clinic: Retrospective validation and future perspectives

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Advancement in Human Face Prediction Using DNA

Alshehhi, A., Almarzooqi, A., Alhammadi, K., Werghi, N., Tay, G. K., & AlSafar, H. S. (2023) · Genes · doi:10.3390/genes14010136 · Cited by 18 · see citing works

CUX1-related neurodevelopmental disorder: deep insights into phenotype-genotype spectrum and underlying pathology

Oppermann, H., Marcos-Grañeda, E., Weiss, L. A., Gurnett, C. A., Jelsig, A. M., Vineke, S. H., Isidor, B., Mercier, S., Magnussen, K., Zacher, P., et al. (2023) · European Journal of Human Genetics · doi:10.1038/s41431-023-01445-2 · Cited by 18 · see citing works

GestaltGAN: synthetic photorealistic portraits of individuals with rare genetic disorders

Kirchhoff, A., Hustinx, A., Javanmardi, B., Hsieh, T., Brand, F., Hellmann, F., Mertes, S., André, E., Moosa, S., Schultz, T., et al. (2025) · European Journal of Human Genetics · doi:10.1038/s41431-025-01787-z · Cited by 18 · see citing works

Assessing DxGPT: Diagnosing Rare Diseases with Various Large Language ModelsPreprint

do Olmo, J., Logroño, J., Mascías, C., Martínez, M., & Isla, J. (2024) · medRxiv · doi:10.1101/2024.05.08.24307062 · Cited by 17 · see citing works

Comparing 2D and 3D representations for face-based genetic syndrome diagnosis

Bannister, J. J., Wilms, M., Aponte, J. D., Katz, D. C., Klein, O. D., Bernier, F. P., Spritz, R. A., Hallgrímsson, B., & Forkert, N. D. (2023) · European Journal of Human Genetics · doi:10.1038/s41431-023-01308-w · Cited by 16 · see citing works

Face-based machine learning diagnostics: applications, challenges and opportunities

Song, J., He, M., Zheng, X., Zhang, Y., Bi, C., Feng, J., Du, J., Li, H., & Shen, B. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11246-2 · Cited by 15 · see citing works

Static and Motion Facial Analysis for Craniofacial Assessment and Diagnosing Diseases

Matthews, H. S., de Jong, G., Maal, T., & Claes, P. D. (2022) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-122120-111413 · Cited by 15 · see citing works

The future role of facial image analysis in ACMG classification guidelines

Lesmann, H., Klinkhammer, H., & Krawitz, P. D. M. D. P. P. M. (2023) · Medizinische Genetik · doi:10.1515/medgen-2023-2014 · Cited by 14 · see citing works

Genetic counselors' utilization of ChatGPT in professional practice: A cross‐sectional study

Ahimaz, P. R., Bergner, A. L., Florido, M. E., Harkavy, N., & Bhattacharyya, S. (2023) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.63493 · Cited by 13 · see citing works

Approximating facial expression effects on diagnostic accuracy via generative AI in medical genetics

Patel, T., Othman, A. A., Sümer, Ö., Hellman, F., Krawitz, P. M., André, E., Ripper, M. E., Fortney, C., Persky, S., Hu, P., et al. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae239 · Cited by 12 · see citing works

Next-generation phenotyping integrated in a national framework for patients with ultra-rare disorders improves genetic diagnostics and yields new molecular findingsPreprint

Schmidt, A., Danyel, M., Grundmann, K., Brunet, T., Klinkhammer, H., Hsieh, T., Engels, H., Peters, S., Knaus, A., Moosa, S., et al. (2023) · medRxiv · doi:10.1101/2023.04.19.23288824 · Cited by 12 · see citing works

ZSCAN10 deficiency causes a neurodevelopmental disorder with characteristic oto-facial malformations

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Loss‐of‐Function Variants in CUL3 Cause a Syndromic Neurodevelopmental Disorder

Blackburn, P. R., Ebstein, F., Hsieh, T., Motta, M., Radio, F. C., Herkert, J. C., Rinne, T., Thiffault, I., Rapp, M., Alders, M., et al. (2024) · Annals of Neurology · doi:10.1002/ana.27077 · Cited by 11 · see citing works

Big data and transformative bioinformatics in genomic diagnostics and beyond

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Building Trust in the Application of Machine Learning Algorithms for Rare Disease Diagnosis

Lembo, L., Barra, M., & Iriti, A. (2023) · Asian Journal of Ethics in Health and Medicine · doi:10.51847/mo7nxmibna · Cited by 11 · see citing works

Biallelic variants in the noncoding RNA gene RNU4-2 cause a recessive neurodevelopmental syndrome with distinct white matter changes

Rius, R., Blakes, A. J. M., Chen, Y., Jonghe, J. D., Lecoquierre, F., Dawes, R., Cogné, B., Kim, H. C., Alvi, J. R., Amblard, F., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02554-6 · Cited by 10 · see citing works

Artificial intelligence and the impact on medical genetics

Solomon, B. D., & Chung, W. K. (2023) · American Journal of Medical Genetics Part C Seminars in Medical Genetics · doi:10.1002/ajmg.c.32060 · Cited by 10 · see citing works

Syndrome-informed phenotyping identifies a polygenic background for achondroplasia-like facial variation in the general population

Vanneste, M., Hoskens, H., Goovaerts, S., Matthews, H. S., Devine, J., Aponte, J. D., Cole, J. B., Shriver, M. D., Marazita, M. L., Weinberg, S. M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54839-1 · Cited by 10 · see citing works

Breaking barriers: fostering equitable access to pediatric genomics through innovative care models and technologies

Jenkins, S. M., Palmquist, R. N., Shayota, B. J., Solorzano, C. M., Bonkowsky, J. L., Estabrooks, P. A., & Tristani‐Firouzi, M. (2025) · Pediatric Research · doi:10.1038/s41390-025-03859-8 · Cited by 10 · see citing works

Artificial intelligence-driven genotype–epigenotype–phenotype approaches to resolve challenges in syndrome diagnostics

Mak, C. C. Y., Klinkhammer, H., Choufani, S., Reko, N., Christman, A. K., Pisan, É., Chui, M. M. C., Lee, M., Leduc, F., Dempsey, J. C., et al. (2025) · EBioMedicine · doi:10.1016/j.ebiom.2025.105677 · Cited by 10 · see citing works

Combined genome-wide association study of facial traits in Europeans increases explained variance and improves prediction

Xiong, Z., Li, Y., Liu, X., Lu, H., Hysi, P. G., Pardo, L. M., Uitterlinden, A. G., Rivadeneira, F., Ikram, M. A., Ghanbari, M., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-61761-7 · Cited by 10 · see citing works

Computational facial analysis for rare Mendelian disorders

Hsieh, T., & Krawitz, P. M. (2023) · American Journal of Medical Genetics Part C Seminars in Medical Genetics · doi:10.1002/ajmg.c.32061 · Cited by 10 · see citing works

Integration of EpiSign , facial phenotyping, and likelihood ratio interpretation of clinical abnormalities in the re‐classification of an ARID1B missense variant

Forwood, C., Ashton, K. A., Zhu, Y., Zhang, F., Dias, K., Standen, K., Evans, C., Carey, L., Cardamone, M., Shalhoub, C., et al. (2023) · American Journal of Medical Genetics Part C Seminars in Medical Genetics · doi:10.1002/ajmg.c.32056 · Cited by 10 · see citing works

Generative Methods for Pediatric Genetics EducationPreprint

Waikel, R. L., Othman, A. A., Patel, T., Hanchard, S. E. L., Hu, P., Tekendo‐Ngongang, C., Duong, D., & Solomon, B. D. (2023) · medRxiv · doi:10.1101/2023.08.01.23293506 · Cited by 10 · see citing works

Perspectives on the Current and Future State of Artificial Intelligence in Medical Genetics

Solomon, B. D., Cheatham, M., de Guimarães, T. A. C., Duong, D., Haendel, M. A., Hsieh, T., Javanmardi, B., Johnson, B. A., Krawitz, P. M., Kruszka, P. S., et al. (2025) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.64118 · Cited by 9 · see citing works

Refining nosology by modelling variation among facial phenotypes: the RASopathies

Matthews, H. S., Vanneste, M., Katsura, K. A., Aponte, D., Patton, M. A., Hammond, P., Baynam, G. S., Spritz, R. A., Klein, O. D., Hallgrímsson, B., et al. (2022) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2021-108366 · Cited by 9 · see citing works

Epigenomic and phenotypic characterization of DEGCAGS syndrome

Karimi, K., Weis, D., Aukrust, I., Hsieh, T., Horackova, M., Paulsen, J., Mendoza‐Londono, R., Dupuis, L., Dickson, M., Lesmann, H., et al. (2024) · European Journal of Human Genetics · doi:10.1038/s41431-024-01702-y · Cited by 9 · see citing works

Next‐generation phenotyping contributing to the identification of a 4.7 kb deletion in KANSL1 causing Koolen‐de Vries syndrome

Brand, F., Vijayananth, A., Hsieh, T., Schmidt, A., Peters, S., Mangold, E., Cremer, K., Bender, T. T. A., Sivalingam, S., Hundertmark, H., et al. (2022) · Human Mutation · doi:10.1002/humu.24467 · Cited by 9 · see citing works

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

Sümer, Ö., Hellmann, F., Hustinx, A., Hsieh, T., André, E., & Krawitz, P. M. (2023) · Studies in health technology and informatics · doi:10.3233/shti230312 · Cited by 9 · see citing works

Loss-of-function variants in CUL3 cause a syndromic neurodevelopmental disorderPreprint

Blackburn, P. R., Ebstein, F., Hsieh, T., Motta, M., Radio, F. C., Herkert, J. C., Rinne, T., Thiffault, I., Rapp, M., Alders, M., et al. (2023) · medRxiv · doi:10.1101/2023.06.13.23290941 · Cited by 9 · see citing works

Künstliche Intelligenz bei der Diagnose Seltener Erkrankungen: die Entwicklung der Phänotyp-Analyse

Krawitz, P. M. (2022) · Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz · doi:10.1007/s00103-022-03602-2 · Cited by 8 · see citing works

Rare Genetic Developmental Disabilities: Mabry Syndrome (MIM 239300) Index Cases and Glycophosphatidylinositol (GPI) Disorders

Thompson, M. D., & Knaus, A. (2024) · Genes · doi:10.3390/genes15050619 · Cited by 8 · see citing works

Automated Multi-Class Facial Syndrome Classification Using Transfer Learning Techniques

Sherif, F. F., Tawfik, N., Mousa, D., Abdallah, M. S., & Cho, Y. I. (2024) · Bioengineering · doi:10.3390/bioengineering11080827 · Cited by 7 · see citing works

Facial clues to the photosensitive trichothiodystrophy phenotype in childhood

Pascolini, G., Gaudioso, F., Baldi, M., Alario, D., Dituri, F., Novelli, A., & Baban, A. (2023) · Journal of Human Genetics · doi:10.1038/s10038-023-01134-4 · Cited by 7 · see citing works

Potential of Artificial Intelligence to Accelerate Drug Development for Rare Diseases

Napolitano, G., Has, C., Schwerk, A. M. K., Yuan, J.-H., & Ullrich, C. (2024) · Pharmaceutical Medicine · doi:10.1007/s40290-023-00504-9 · Cited by 7 · see citing works

Fostering Tomorrow: Uniting Artificial Intelligence and Social Pediatrics for Comprehensive Child Well-being

Gülşen, M., & Yalçın, S. S. (2024) · Turkish Archives of Pediatrics · doi:10.5152/turkarchpediatr.2024.24076 · Cited by 7 · see citing works

Case Report: The success of face analysis technology in extremely rare genetic diseases in Korea: Tatton–Brown–Rahman syndrome and Say–Barber –Biesecker–Young–Simpson variant of ohdo syndrome

Park, S., Kim, J., Song, T., & Jang, D. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.903199 · Cited by 7 · see citing works

Expanding the Phenotypic spectrum of NAA10 -related neurodevelopmental syndrome and NAA15 -related neurodevelopmental syndromePreprint

Lyon, G. J., Vedaie, M., Besheim, T., Park, A. Y., Marchi, E. J., Gottlieb, L., Hsieh, T., Klinkhammer, H., Sandomirsky, K., Cheng, H., et al. (2022) · medRxiv · doi:10.1101/2022.08.22.22279061 · Cited by 7 · see citing works

Unveiling the crucial neuronal role of the proteasomal ATPase subunit gene <i>PSMC5</i> in neurodevelopmental proteasomopathies

Küry, S., Stanton, J. E., van Woerden, G., Hsieh, T.-C., Rosenfelt, C., Scott-Boyer, M. P., Most, V., Wang, T., Papendorf, J. J., de Konink, C., et al. (2024) · doi:10.1101/2024.01.13.24301174 · Cited by 6 · see citing works

Evaluation of a New Inclusive Next‐Generation Synthetic Face Tool for Dysmorphology

Bénichou, L., Breton, L., Garcelon, N., Benichou, B., Lienhard, O., Amiel, J., Bongibault, T., Hidalgo, Á., Cormier‐Daire, V., Lyonnet, S., et al. (2025) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.64298 · Cited by 6 · see citing works

Molecular genotype-phenotype correlation in ACTB- and ACTG1-related non-muscle actinopathies

Donato, N. D., Thom, A., Rump, A., Greve, J. N., Cadiñanos, J. E., Calabrò, R. S., Cathey, S. E., Chung, B., Cope, H., Costales, M., et al. (2026) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.12.007 · Cited by 6 · see citing works

Facial features of lysosomal storage disorders

D’Souza, A., Ryan, E., & Sidransky, E. (2022) · Expert Review of Endocrinology & Metabolism · doi:10.1080/17446651.2022.2144229 · Cited by 6 · see citing works

The future of commercial genetic testing

Solomon, B. D. (2023) · Current Opinion in Pediatrics · doi:10.1097/mop.0000000000001260 · Cited by 6 · see citing works

Comparison of clinical geneticist and computer visual attention in assessing genetic conditions

Duong, D., Johny, A. R., Hanchard, S. E. L., Fortney, C., Flaharty, K. A., Hellmann, F., Hu, P., Javanmardi, B., Moosa, S., Patel, T., et al. (2024) · PLoS Genetics · doi:10.1371/journal.pgen.1011168 · Cited by 6 · see citing works

Homozygous variant in translocase of outer mitochondrial membrane 7 leads to metabolic reprogramming and microcephalic osteodysplastic dwarfism with moyamoya disease

Li, C.-Y., Chen, L., Tsai, M., Chou, Y., Lin, P.-X., Chang, Y.-M., Hwu, W., Chien, Y., Lin, J., Chen, H., et al. (2024) · EBioMedicine · doi:10.1016/j.ebiom.2024.105476 · Cited by 6 · see citing works

Pathogenic de novo variants in PPP2R5C cause a neurodevelopmental disorder within the Houge-Janssens syndrome spectrum

Verbinnen, I., Douzgou, S., Hsieh, T., Lesmann, H., Kirchhoff, A., Geneviève, D., Brimble, E., Lenaerts, L., Haesen, D., Levy, R. J., et al. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.01.021 · Cited by 6 · see citing works

Neuroanatomical features of NAA10 and NAA15-related neurodevelopmental syndromes

Patel, R., Makwana, R., Christ, C., Marchi, E. J., Ung, N., Harpell, R., Miyake, C. Y., Gropman, A. L., Lyon, G. J., & Whitehead, M. T. (2025) · Journal of Neuroradiology · doi:10.1016/j.neurad.2025.101339 · Cited by 6 · see citing works

Molecular and clinical aspects of histone-related disorders

Ojaimi, M. A., Banimortada, B. J., Alragheb, A., Hajir, R. S., Alves, C., Walid, D., Raza, A., & El-Hattab, A. E. (2025) · Human Genomics · doi:10.1186/s40246-025-00734-9 · Cited by 3 · see citing works

Exome Sequencing Identifies Multiple Genetic Diagnoses in Children with Syndromic Growth Disorders

Rezende, R. C., Andrade, N. L. M. D., Dantas, N. C. B., Cellin, L. D. P., Krepischi, A. C. V., Lerário, A. M., & Jorge, A. A. L. (2023) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2023.113841 · Cited by 6 · see citing works

PhenoScore: AI-based phenomics to quantify rare disease and genetic variationPreprint

Dingemans, A. J. M., Hinne, M., Truijen, K. M. G., Goltstein, L. C. M. J., van Reeuwijk, J., de Leeuw, N., Schuurs-Hoeijmakers, J. H. M., Pfundt, R., Diets, I. J., den Hoed, J., et al. (2022) · medRxiv · doi:10.1101/2022.10.24.22281480 · Cited by 6 · see citing works

Potential of facial biomarkers for Alzheimer's disease and obstructive sleep apnea in Down syndrome and general population

Echeverry, L. M., Llambrich, S., Heredia-Lidón, Á., Giménez, S., Aranha, M. R., Inampudi, P., Heuzé, Y., Sevillano, X., Fortea, J., Martínez‐Abadías, N., et al. (2025) · The FASEB Journal · doi:10.1096/fj.202403009r · Cited by 5 · see citing works

A call for implementing augmented intelligence in pediatric dermatology

Issa, C. J., Reimer‐Taschenbrecker, A., & Paller, A. S. (2023) · Pediatric Dermatology · doi:10.1111/pde.15298 · Cited by 5 · see citing works

A diagnostic support system based on pain drawings: binary and k-disease classification of EDS, GBS, FSHD, PROMM, and a control group with Pain2D

Emmert, D., Szczypien, N., Bender, T. T. A., Grigull, L., Gass, A., Link, C., Klawonn, F., Conrad, R., Mücke, M., & Sellin, J. (2023) · Orphanet Journal of Rare Diseases · doi:10.1186/s13023-023-02663-z · Cited by 5 · see citing works

Comprehensive genetic testing approaches as the basis for personalized management of growth disturbances: current status and perspectives

van der Kaay, D. C. M., Rochtus, A. M., Binder, G., Kurth, I., Prawitt, D., Netchine, I., Johannsson, G., Hokken‐Koelega, A. C. S., Elbracht, M., & Eggermann, T. (2022) · Endocrine Connections · doi:10.1530/ec-22-0277 · Cited by 5 · see citing works

Facial appearance associates with longitudinal multi-organ failure: an ICU cohort study

Cox, E. G. M., van der Horst, I. C. C., Llamazares, N. C., Sels, J.-W. E. M., Onrust, M., van der Horst, I. C. C., Koeze, J., SICS Study Group, Koster, G., Koeze, J., et al. (2024) · Critical Care · doi:10.1186/s13054-024-04891-6 · Cited by 5 · see citing works

A 3D Clinical Face Phenotype Space of Genetic Syndromes Using a Triplet-Based Singular Geometric Autoencoder

Mahdi, S. S., Caldeira, E., Matthews, H. S., Vanneste, M., Nauwelaers, N., Yuan, M., Gong, S., Bouritsas, G., Baynam, G. S., Hammond, P., et al. (2024) · IEEE Access · doi:10.1109/access.2024.3524428 · Cited by 5 · see citing works

A deep learning transformer model predicts high rates of undiagnosed rare disease in large electronic health systemsPreprint

Jordan, D. M., Vy, H. M. T., & Do, R. (2023) · medRxiv · doi:10.1101/2023.12.21.23300393 · Cited by 7 · see citing works

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

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O17: GestaltMatcher supports classification of ultra-rare disorders and delineation of novel syndromes by facial phenotype descriptors*

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