Publications using Face2Gene
Bibliography / References (updated as of May 2023) Case Studies
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Echeverry-Quiceno, L.M., Candelo, E., Gómez, E. et al. Population-specific facial traits and diagnosis accuracy of genetic and rare diseases in an admixed Colombian population. Sci Rep 13, 6869 (2023). https://doi.org/10.1038/s41598-023-33374-x
Ciancia, S., Goedegebuure, W.J., Grootjen, L.N. et al. Computer-aided facial analysis as a tool to identify patients with Silver–Russell syndrome and Prader–Willi syndrome. Eur J Pediatr (2023). https://doi.org/10.1007/s00431-023-04937-x
Pascolini, G., Gaudioso, F., Baldi, M. et al. Facial clues to the photosensitive trichothiodystrophy phenotype in childhood. J Hum Genet 68, 437–443 (2023). https://doi.org/10.1038/s10038-023-01134-4
2022). Expansion of the genotypic and phenotypic spectrum of CTCF-related disorder guides clinical management: 43 new subjects and a comprehensive literature review. American Journal of Medical Genetics Part A, 1– 12. https://doi.org/10.1002/ajmg.a.63065, , , , , & (
2022). The utility of DNA methylation signatures in directing genome sequencing workflow: Kabuki syndrome and CDK13-related disorder. American Journal of Medical Genetics Part A, 188A: 1368– 1375 doi.org/10.1002/ajmg.a.62650, , , , , , , , & (
Cousin, M.A., Veale, E.L., Dsouza, N.R. et al. (2022) Gain and loss of TASK3 channel function and its regulation by novel variation cause KCNK9 imprinting syndrome. Genome Med 14, 62. doi.org/10.1186/s13073-022-01064-4
Nagy D, Verheyen S, Wigby KM, Borovikov A, Sharkov A, et al. (2022) Genotype-Phenotype Comparison in POGZ-Related Neurodevelopmental Disorders by Using Clinical Scoring. Genes. 2022; 13(1):154. https://doi.org/10.3390/genes13010154
Schoeman, L., Honey, E.M., Malherbe, H. et al.(2022) Parents’ perspectives on the use of children’s facial images for research and diagnosis: a survey. J Community Genet 13, 641–654 https://doi.org/10.1007/s12687-022-00612-0
Guo, L., Park, J., Yi, E. et al. (2022) KBG syndrome: videoconferencing and use of artificial intelligence driven facial phenotyping in 25 new patients. Eur J Hum Genet (2022). https://doi.org/10.1038/s41431-022-01171-1
Park S, Kim J, Song T-Y and Jang D-H (2022) 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. Front. Genet. 13:903199. doi: 10.3389/fgene.2022.903199
Pascolini G, Calvani M, Grannatico P (2022) First Italian experience using the automated craniofacial gestalt analysis on a cohort of pediatric patients with multiple anomaly syndromesItal J Pediatr. 2022 Jun 13;48(1):91. doi: 10.1186/s13052-022-01283-w. PMID: 35698205; PMCID: PMC9195312
Qiang J, Wu D, Du H, Zhu H, Chen S, Pan H. (2022) Review on Facial-Recognition-Based Applications in Disease Diagnosis. Bioengineering. 2022; 9(7):273. doi.org/10.3390/bioengineering9070273
Mensah MA., Ott C., Horn D., Pantel JT. (2022) A machine learning-based screening tool for genetic syndromes in childrenvolume 4, issue 5, E295, May 01, 2022
Merico P., Huang-Doran I., Al-Naqeb D., et al. (2022) Biallelic POC1A variants cause syndromic severe insulin resistance with muscle cramps. European Society of Endocrinology, Volume 186, Issue 5.doi.org/10.1530/EJE-21-0609
Elmas M., Gogus B. (2022). The road from mutation to next generation phenotyping: contribution of deep learning technology (Face2Gene) to diagnosis neurofibromatosis type 1. The European Research Journal, Volume 8, Issue 2, 145 – 154. doi.org/10.18621/eurj.894631
Riedhammer K. M., Burgemeister AL., Cantagrel V., et al. (2022) Suleiman-El-Hattab syndrome: a histone modification disorder caused by TASP1 deficiency. Hum Mol Genet. 2022 May 5. doi.org/10.1093/hmg/ddac098
Asif M., Kaygusuz E., Shinawi M., et al. (2022) De novo variants of CSNK2B cause a new intellectual disability-craniodigital syndrome by disrupting the canonical Wnt signaling pathway. HGG Advances, Volume 3, Issue 3. doi.org/10.1016/j.xhgg.2022.100111
Li X., Yao R., Chang G., et al. (2022) Clinical Profiles and Genetic Spectra of 814 Chinese Children With Short Stature. The Journal of Clinical Endocrinology & Metabolism, Volume 107, Issue 4, April 2022, Pages 972–985, doi.org/10.1210/clinem/dgab863
Micale L., Morlino S., Carbone A., et al. (2022) Loss-of-function variants in exon 4 of TAB2 cause a recognizable multisystem disorder with cardiovascular, facial, cutaneous, and musculoskeletal involvement. Genet Med. 2022 Feb; 24(2):439-453. doi.org/10.1016/j.gim.2021.10.009
Nagy D., Verheyen S., Wigby KM., et al. (2022) Genotype-Phenotype Comparison in POGZ-Related Neurodevelopmental Disorders by Using Clinical Scoring. Genes, volume 13, issue 1, page 154. doi.org/10.3390/genes13010154
Daykin E., Fleischer N., Abdelwahab M, Hassib N., Schiffmann R., Ryan E., Sidransky E. (2021). Investigation of a dysmorphic facial phenotype in patients with Gaucher disease types 2 and 3 , Molecular Genetics and Metabolism, ISSN 1096-7192, doi.org/10.1016/j.ymgme.2021.09.008
Priol A-C, Denis L, Boulanger G, Thépaut M, Geoffray M-M, Tordjman S. (2021) Detection of Morphological Abnormalities in Schizophrenia: An Important Step to Identify Associated Genetic Disorders or Etiologic Subtype s. International Journal of Molecular Sciences. 2021; 22(17):9464. /doi.org/10.3390/ijms22179464
2021) Things are not always what they seem: From Cornelia de Lange to KBG phenotype in a girl with genetic variants in NIPBL and ANKRD11 . Molecular Genetics & Genomic Medicine, 00, e1826. doi.org/10.1002/mgg3.1826, , et al. (
2021). Next-generation phenotyping in cat-eye syndrome based on computer-aided facial dysmorphology analysis of normal photographs. Molecular Genetics & Genomic Medicine. doi.org/10.1002/mgg3.1785, , (
Javitt, M.J., Vanner, E.A., Grajewski, A.L. et al. (2021) Evaluation of a computer-based facial dysmorphology analysis algorithm (Face2Gene) using standardized textbook photos. Eye. doi.org/10.1038/s41433-021-01563-5
The point‐of‐care use of a facial phenotyping tool in the genetics clinic: Enhancing diagnosis and education with machine learning . Am J Med Genet Part A. 2021; 1– 8. https://doi.org/10.1002/ajmg.a.62092, , , , . (2021)
Körber, L., Schneider, H., et al. (2021) No evidence for preferential X-chromosome inactivation as the main cause of divergent phenotypes in sisters with X-linked hypohidrotic ectodermal dysplasia . Orphanet J Rare Dis 16, 98 (2021). https://doi.org/10.1186/s13023-021-01735-2
Zarate, Y.A., Bosanko, K.A., Thomas, M.A. et al. (2021) Growth, development, and phenotypic spectrum of individuals with deletions of 2q33.1 involvingSATB2. Clinical Genetics. https://doi.org/10.1111/cge.13912
Stamberger, H., Hammer, T.B., Gardella, E. et al. (2020) NEXMIF encephalopathy: an X-linked disorder with male and female phenotypic patterns. Genet Med (2020). https://doi.org/10.1038/s41436-020-00988-9
Rubinstein–Taybi syndrome in diverse populations. Am J Med Genet Part A. 2020; 1– 12. https://doi.org/10.1002/ajmg.a.61888, , , et al. (2020)
Molecular and phenotypic spectrum of Noonan syndrome in Chinese patients . Clin Genet. 2019; 96: 290– 299. https://doi.org/10.1111/cge.13588, , , et al. (2020)
Gomez D, Bird L.M , Fleischer N, Abdul-Rahman O.A.(2020) Differentiating Molecular Etiologies of Angelman Syndrome Through Facial Phenotyping Using Deep Learning. Am J Med Genet Part A. 2020; DOI:10.1002/ajmg.a.61720
Noonan syndrome on the African Continent. Birth Defects Research. 2020; 112: 718– 724. https://doi.org/10.1002/bdr2.1675, . (2020)
Gonzalez Garcia et al. (2020) A novel mosaic variant on SMC1A reported in buccal mucosa cells, albeit not in blood, of a patient with Cornelia de Lange–like presentation. Cold Spring Harb Mol Case Stud 6: a005322
Pascolini, G., Agolini, E., Fleischer, N. et al.(2020) Further delineation of the neurodevelopmental phenotypic spectrum associated to 14q11.2 microduplication. Neurol Sci (2020). https://doi.org/10.1007/s10072-020-04510-6
Tripon F.; Bogliș, A.; Micheu, C.; Streață, I.; Bănescu, C. (2020) Pitt-Hopkins Syndrome: Clinical and Molecular Findings of a 5-Year-Old Patient. Genes 2020, 11, 596.
Agbolade, O.; Nazri, A.; Yaakob, R.; Ghani, A.A.; Cheah, Y.K. (2020) Down Syndrome Face Recognition: A Review. Symmetry 2020, 12, 1182.
Pode-Shakked B., Finezilber Y, Levi Y., Putter S., Fleischer N., Greenbaum L., Raas-Rothschild A.(2020) Shared facial phenotype of patients with Mucolipidosis type IV: a clinical observation reaffirmed by next generation phenotyping. Eu Journal of Medical Genettics:EJMG_2020_5_R1
A novel patient with White–Sutton syndrome refines the mutational and clinical repertoire of the POGZ‐related phenotype and suggests further observations . Am J Med Genet Part A. 2020; 1– 5. https://doi.org/10.1002/ajmg.a.61605, , , et al.(2020)
Cappuccio, G., Sayou, C., Tanno, P.L. et al.(2020) De novo SMARCA2 variants clustered outside the helicase domain cause a new recognizable syndrome with intellectual disability and blepharophimosis distinct from Nicolaides–Baraitser syndrome . Genet Med (2020). https://doi.org/10.1038/s41436-020-0898-y
Kumps, C.; Campos-Xavier, B.; Hilhorst-Hofstee, Y.; Marcelis, C.; Kraenzlin, M.; Fleischer, N.; Unger, S.; Superti-Furga, A.(2020) T he Connective Tissue Disorder Associated with Recessive Variants in the SLC39A13 Zinc Transporter Gene (Spondylo-Dysplastic Ehlers–Danlos Syndrome Type 3): Insights from Four Novel Patients and Follow-Up on Two Original Cases . Genes 2020, 11, 420.
Jezela-Stanek, A.; Ciara, E.; Stepien, K.M. (2020) Neuropathophysiology, Genetic Profile, and Clinical Manifestation of Mucolipidosis IV—A Review and Case Series. Int. J. Mol. Sci. 2020, 21, 4564.
Pascolini G. (2020) DeepGestalt analysis of the SETD5-associated intellectual disability syndrome. J Transl Genet Genom 2020;4:17-21. http://dx.doi.org/10.20517/jtgg.2020.05
Myers L, Anderlid B-M, Nordgren A,et al.(2020) Clinical versus automated assessments of morphological variants in twins with and without neurodevelopmental disorders. Am J Med Genet Part A. 2020;1–13. https://doi.org/10.1002/ajmg.a.61545
Arora V, Puri RD, Bijarnia-Mahay S, Verma IC.(2020) Expanding the phenotypic and genotypic spectrum of Wiedemann–Steiner syndrome: First patient from India. Am J Med Genet Part A. 2020;1–4. https://doi.org/10.1002/ajmg.a.61534
Basel, D (2020) Dysmorphology in a Genomic Era. Clinics in Perinatology, Volume 47, Issue 1, 15-23
Gurovich Y (2020) The Path to and Impact of Disease Recognition with AI in IEEE Pulse, vol. 11, no. 1, pp. 13-16, Jan.-Feb. 2020. doi: 10.1109/MPULS.2020.2972722
Latorre-Pellicer, A., et al. (2020) Evaluating Face2Gene as a Tool to Identify Cornelia de Lange Syndrome by Facial Phenotypes. Int. J. Mol. Sci. 2020, 21, 1042
Cuvertino, S., Hartill, V., Colyer, A. et al. (2020) A restricted spectrum of missense KMT2D variants cause a multiple malformations disorder distinct from Kabuki syndrome. Genet Med (2020). https://doi.org/10.1038/s41436-019-0743-3
Elmas M, Gogus B (2020) Success of Face Analysis Technology in Rare Genetic Diseases Diagnosed by Whole-Exome Sequencing: A Single-Center Experience. Mol Syndromol 2020. doi: 10.1159/000505800
Bijarnia-Mahay S, Arora V. (2020) Next Generation Clinical Practice – It’s Man Versus Artificial Intelligence!. Indian Pediatr. 2019;56(12):1007–1008.
Narayanan, Dhanya & Ranganath, Prajnya & Aggarwal, Shagun & Dalal, Ashwin & Phadke, Shubha & Mandal, Kaushik. (2020). Computer-aided Facial Analysis in Diagnosing Dysmorphic Syndromes in Indian Children . Indian Pediatrics. 56. 1017-1019. 10.1007/s13312-019-1682-4.
Turner syndrome in diverse populations. Am J Med Genet Part A. 2019; 1– 11. https://doi.org/10.1002/ajmg.a.61461, , , et al.(2019)
Soo Kyoung Kim, So Yoon Jung, Seong Phil Bae1, Jieun Kim, Jeongho Lee, Dong Hwan Lee (2019) A case of Noonan syndrome diagnosed using the facial recognition software (Face2Gene)
Journal of Genetic Medicine 2019;16:81-84 https://doi.org/10.5734/JGM.2019.16.2.81
Zarate YA, Bosanko KA, Gripp KW (2019) Using facial analysis technology in a typical genetic clinic:
experience from 30 individuals from a single institution Journal of Human Genetics 1435-232X doi.org/10.1038/s10038-019-0673-6
Pascolini G, ValiantevM, Bottillo I, Laino I, Fleischer N, Ferrari A, Grammatico P (2019) Striking phenotypic overlap between Nicolaides-Baraitser and Coffin-Siris syndromes in monozygotic twins with ARID1B intragenic deletion . Eur J Med Genet. 2019 Aug 14:103739. doi: 10.1016/j.ejmg.2019.103739.
Weiss k, Lazar HP […] Lachlan K (2019) The CHD4-related syndrome: a comprehensive investigation of the clinical spectrum, genotype–phenotype correlations, and molecular basis. Genetics in Medicine 1530-0366 https://doi.org/10.1038/s41436-019-0612-0
Kruszka P, Hu T, Hong S, […] Muenke M et al. (2019) Phenotype delineation of ZNF462 related syndrome.
Am J Med Genet Part A. 2019; 1– 8. https://doi.org/10.1002/ajmg.a.61306
Fung JLF, Rethanavelu K, Luk HM, Ho MSP, Lo IFM, Chung BHY (2019) Coffin-Lowry syndrome in Chinese.
Am J Med Genet A. 2019 Aug 9. doi: 10.1002/ajmg.a.61323. [Epub ahead of print]
Danyel M, Cheng Z, Jung C, Boschann F, […] Mensah M (2019) Differentiation of MISSLA and Fanconi anaemia by computer-aided image analysis and presentation of two novel MISSLA siblings . European Journal of Human Genetics https://doi.org/10.1038/s41431-019-0469-3
Knaus A, Kortüm F, Kleefstra T, Stray-Pedersen A, Dukić D, Murakami Y, Gerstner T, van Bokhoven H, Iqbal Z, Horn D, Kinoshita T, Hempel M, Krawitz PM.(2019) Mutations in PIGU Impair the Function of the GPI Transamidase Complex, Causing Severe Intellectual Disability, Epilepsy, and Brain Anomalies . Am J Hum Genet. 2019 Jul 18. pii: S0002-9297(19)30234-4. doi: 10.1016/j.ajhg.2019.06.009.
Hsieh TC, Mensah MA, […] Krawitz PM (2019) PEDIA: prioritization of exome data by image analysis. Genetics in Medicine https://doi.org/10.1038/s41436-019-0566-2
Pascolini G, Fleischer N, Ferraris A, Majore S, Grammatico P. (2019) The facial dysmorphology analysis technology in intellectual disability syndromes related to defects in the histones modifiers. Journal of Human Genetics, SN-1435-32X https://doi.org/10.1038/s10038-019-0598-0
Mishima H, Suzuki H, Doi M, Miyazaki M, Watanabe S, Matsumoto T, Morifuji K, Moriuchi H, Yoshiura K, Kondoh T, Kosaki K. (2019) Evaluation of Face2Gene using facial images of patients with congenital dysmorphic syndromes recruited in Japan. Journal of Human Genetics 1435-232X https://doi.org/10.1038/s10038-019-0619-z
Bayat A, Knaus A,Wollenberg A, et al. (2019) PIGT-CDG, a disorder of the glycosylphosphatidylinositol anchor: description of 13 novel patients and expansion of the clinical characteristics. Genetics in Medicine SN – 1530-0366, https://doi.org/10.1038/s41436-019-0512-3
Carli D, Giorgio E, Pantaleoni F, Bruselles A, Barresi S, Riberi E, Licciardi F, Gazzin A, Baldassarre G, Pizzi S, Niceta M, Radio FC, Molinatto C, Montin D, Calvo PL, Ciolfi A, Fleischer N, Ferrero GB, Brusco A, Tartaglia M. (2019) NBAS pathogenic variants: Defining the associated clinical and facial phenotype and genotype–phenotype correlations. Human Mutation. 2019; 1– 8. https://doi.org/10.1002/humu.23734
Marbach F, Rustad C, Riess A,Netzer C. (2019) The Discovery of a LEMD2-Associated Nuclear Envelopathy with Early Progeroid Appearance Suggests Advanced Applications for AI-Driven Facial Phenotyping, Am J Hum Gene https://doi .org/10.1016/j.ajhg.2019.02.021
**Gurovich Y, Hanani Y, Bar O, Nadav G, Fleischer N, Gelbman D, Basel-Salmon L, Krawitz PM, Kamphausen SB, Zenker M, Bird LM, Gripp KW. (2019) Identifying facial phenotypes of genetic disorders using deep learning. Nature Medicine 25, pages 60–64 DOI:10.1038/s41591-018-0279-0
Martinez-Monseny A,Cuadras D, Bolasell M, et al. (2018) From gestalt to gene: early predictive dysmorphic features of PMM2-CDG J Med Genet doi:10.1136/jmedgenet-2018-105588
Shia W, Chena Y, Chena S, Lia S, Changa C, Zhanga L, Feia H, Huanga H, Zhanga J, Xua C,(2018) Integrated facial analysis and targeted sequencing identifies a novel KDM6A pathogenic variant resulting in Kabuki syndrome . Journal of Bio-X Research 1:140–146 http://dx.doi.org/10.1097/JBR.0000000000000022
Amudhavalli SM, Hanson R, Angle B, Bontempo K, Gripp KW. (2018) Further delineation of Aymé‐Gripp syndrome and use of automated facial analysis tool. Am J Med Genet Part A.2018;176A:1648 1656 doi.org/10.1002/ajmg.a.38832
Vorravanpreecha N, Lertboonnum T, Rodjanadit R, Sriplienchan P, Rojnueangnit K, (2018) Studying Down syndrome recognition probabilities in Thai children with de‐identified computer‐aided facial analysis American Journal of Medical Genetics Am J Med Genet Part A. 2018;1–6. https://doi.org/10.1002/ajmg.a.40483
Jiang Y, Wangler MF, McGuire Al, Lupski JR, Posey JE, Khayat MM, Murdock DR, Sanchez‐Pulido L, Ponting CP, Xia F, Hunter JV, Meng Q, Murugan M, Gibbs RA (2018) The phenotypic spectrum of Xia‐Gibbs syndrome Am J Med Genet, V176, I 6, P1315-1326 doi: 10.1002/ajmg.a.38699
Advances in computer-assisted syndrome recognition by the example of inborn errors of metabolism J Inherit Metab Dis (2018). ttps://doi.org/10.1007/s10545-018-0174-3
Hurst, Anna C.E. (2018). Facial recognition software in clinical dysmorphology.Current Opinion in Pediatrics, (),1–. doi:10.1097/mop.0000000000000677
Natural history and genotype-phenotype correlations in 72 individuals with SATB2-associated syndrome . Am J Med Genet Part A. 2018;1–11. DOI: 10.1002/ajmg.a.38630
Knaus A, Pantel JT, Pendziwiat M., Hajjir, et al.(2018) Characterization of glycosylphosphatidylinositol biosynthesis defects by clinical features, flow cytometry, and automated image analysis. Genome Med. 2018; 10: 3. DOI: 10.1186/s13073-017-0510-5.
Valentine M., Bihm D.C.J., Wolf L, Hoyme H.E., May P.A., Buckley D., Kalberg W., Abdul-Rahman O. (2017) Computer-Aided Recognition of Facial Attributes for Fetal Alcohol Spectrum Disorders . Pediatrics, e20162028; doi: 10.1542/peds.2016-2028.
Liehr T, Acquarola N, Pyle K, St-Pierre S, Rinholm M, Bar O, Wilhelm K, Schreyer I. (2017) Next generation phenotyping in Emanuel and Pallister Killian Syndrome using computer-aided facial dysmorphology analysis of 2D photos. Clin Genet. 2017 Jun 29. doi: 10.1111/cge.13087.
Hadj-Rabia S, Schneider H, Navarro E, Klein O, Kirby N, Huttner K, Wolf L, Orin M, Wohlfart S2, Bodemer C, Grange DK. (2017) Automatic recognition of the XLHED phenotype from facial images. Am J Med Genet A. 2017 ,173(9):2408-2414. doi: 10.1002/ajmg.a.38343. Epub 2017 Jul 10.
Chiu Annie T.G., Zhu Lixing, Gary T.K. Moka, Leung G K.C. , Chowa, C.B. Chung Brian H.Y. (2016) Before and after – Nutritional transformation of dysmorphism in a case of Costello, Eur J Med Genet. 2016 Nov;59(11):573-576.
Gardner OK, Haynes K, Schweitzer D, Johns A, Magee WP, Urata MM, Sanchez-Lara PA. (2016) Familial Recurrence of 3MC Syndrome in Consanguineous Families: A Clinical and Molecular Diagnostic Approach With Review of the Literature. Cleft Palate Craniofac J. 2016 Jun 29. DOI: 10.1597/15-151.
Gripp KW, Baker L, Telegrafi A, Monaghan KG.(2016) The role of objective facial analysis using FDNA in making diagnoses following whole exome analysis. Report of two patients with mutations in the BAF complex genes. Am J Med Genet A. 2016 Apr 26.
Kayembe KT., Kasole LT, Mbuyi-Musanzayi S, Kabamba NL, Katshiez Nawej C, Musa Obadia P, Banza Lubaba Nkulu C, Nemery B, Devriendt K.. (2016), Microtia in Cornelia de Lange syndrome: a case from Democratic Republic of the Congo. Clinical Dysmorpholgy 2016 Oct;25(4):178-8.
Lumaka A, Cosemans N, Lulebo Mampasi A, Mubungu G, Mvuama N, Lubala T, Mbuyi-Musanzayi S, Breckpot J, Holvoet M, De Ravel T, Van Buggenhout G, Peeters H, Donnai D, Mutesa L, Verloes A, Lukusa Tshilobo P, Devriendt K.(2016), Facial dysmorphism is influenced by ethnic background of the patient and of the evaluator Clin Genet . 2016 Dec 7.
Lumaka A, Lukoo R, Mubungu G, Lumpala P, Mbayabo G, Mupuala A, Lukusa Tshilobo P, Devriendt K., (2016) Williams-Beuren syndrome: pitfalls for diagnosis in limited resources setting. Clinical Case Reports 2016 4(3):294-297.
Basel-Vanagaite L, Wolf L, Orin M, Larizza L, Gervasini C, Krantz ID, Deardoff MA. (2016) Recognition of the Cornelia de Lange syndrome phenotype with facial dysmorphology novel analysis. Clin Genet. 2016 May;89(5):557-63.
Face2Gene User Community Includes Users From:
Using Face2Gene to reference all my department’s cases, share information with my colleagues and quickly look up relevant information in the London Medical Databases Online saves me hours of work every week and allows me to focus on my patients.
Dr. Ibrahim Akalin
Assoc. Prof. Ibrahim Akalin, MD, Medical Geneticist from the Istanbul Medeniyet University, Istanbul, Turkey
FDNA’s game-changing technology introduces an objective computer-aided dimension to the “art of dysmorphology”, transforming the analysis into an evidence-based science.
Dr. Michael R. Hayden
Chairman of FDNA’s Scientific Advisory Board & Steering Committee and Editor in Chief of Clinical Genetics
FDNA is developing technology that has the potential to help so many physicians and families by bringing them closer to a diagnosis- there are literally millions of individuals with unusual features around the world that lack a diagnosis and therefore lack information on natural history, recurrence risk and prevention of known complications.
Dr. Judith G. Hall
Professor Emerita of Pediatrics & Medical Genetics UBC & Children's and Women's Health Centre of BC
FDNA has been “right on the money”, providing me with relevant, accurate and insightful information for differential diagnoses.
Dr. Cynthia J.R. Curry
Professor of Pediatrics UCSF, Adjunct Professor of Pediatrics Stanford
I am excited to be a part of the FDNA community, promoting broad information sharing with my peers to amplify the scientific and clinical value of our community’s accumulated knowledge for the purpose of efficiently diagnosing individuals with rare genetic disorders.
Dr. Karen W. Gripp
Chief, Division of Medical Genetics A.I. duPont Hospital for Children
FDNA's idea of incorporating several dysmorphology resources (OMIM, GeneReviews), supported by their visual analytic technology, will be able to improve researching of genetic syndromes - all within a single mobile app.
Dr. Chad Haldeman-Englert
Assistant Professor Pediatrics at Mission Fullerton Genetics
Given the advancement of visual analytical technology, it’s about time Dysmorphology is supported with computational capabilities and moving this to mobile support, is simply the next logical step.
Dr. Chanika Phornphutkul
Associate Professor of Pediatrics Director, Division of Human Genetics Department of Pediatrics Warren Alpert Medical School of Brown University
Having an archive of cases easily accessible from my mobile device anytime and anywhere is a long-time unmet need.
Dr. Lynne Bird
Rady Children's Specialists of San Diego
FDNA's solution is a huge leap forward for dysmorphology. It saves me significant time when I’m evaluating patients in my clinic and provides me with insightful tools that help me generate a differential diagnosis.
Dr. David A. Chitayat
Head of the Prenatal Diagnosis and Medical Genetics Program at Mount Sinai Hospital, Toronto
Shortly after learning about Face2Gene, I’ve started to incorporate this amazing tool into my workflow. Soon enough, Face2Gene’s analysis flushed out references that I would not have considered for several of my patients, which turned out to be their correct diagnosis
Dr. Zvi U. Borochowitz
Chairman (Retired) of The Simon Winter Institute for Human Genetics at Bnai-Zion Medical Center, Technion-Rappaport Faculty of Medicine
The Unknown Forum from Face2Gene is a great community platform for exchanging opinions regarding undiagnosed cases. It is straightforward to use and safe for exchange of medical data, thanks to the efforts of its developers and to the involvement of geneticists worldwide.
Dr. Oana Moldovan
Clinical Geneticist at the Hospital Santa Maria, CHLN, Lisbon, Portugal