NEW: Include features in each of your cases by automatically extracting HPO terms from clinical notes.

How It Works

1) Copy your clinical notes to your case in Face2Gene CLINIC

2) Click the ‘Extract’ button to review the HPO* features and mark as present/absent

*The Human Phenotype Ontology (HPO) provides a standardized vocabulary of phenotypic abnormalities encountered in human disease.

3) Analyze the suggested syndrome matches

Try the BETA* update in Face2Gene CLINIC.

*Available only on desktop, in English

The post Extracting Features From Clinical Notes appeared first on FDNA™.

FDNA’s Face2Gene technology is now being used by more than 70% of clinical geneticists at over 2,000 institutions in 130 countries.

Events & Presentations

• Dr. John Carey & Dr. Christine Stanley – Redefining Phenotyping for Clinical Advancements & Variant Prioritization
• PMWC Duke – Personalizing Medicine with Artificial Intelligence and Facial Analysis
• PMWC Michigan – Big data, next-generation phenotyping, and the possibilities for precision medicine
• Stanford Medicine Big Data In Precision Health – AI in Healthcare: Separating the Hype from the Hope
• Demand Solutions Mexico – Designing A Healthy Society: Facial Recognition Enables Precision Medicine
• HIMSS – Greenwood Genetic’s Journey: Partnering to Improve Precision Medicine 
• ePharma – Using Next-Generation Phenotyping for Precision Medicine Across the Pharma Value Chain
• Dr. John Carey at ACMG – Delineating Genetic Syndromes and Next-Generation Phenotyping
• Dr. Christine Stanley at ACMG – Face2Gene LABS at WuXi NextCODE: Phenotyping for Improved Variant Prioritization
• Dr. Karen Gripp at ACMG – Face2Gene RESEARCH for Deep Phenotyping of Novel Syndromes
• Re:Work – The Road to Precision Medicine: Balancing Ethics and Efficiency
• ThinkGenetic & FDNA – The Genomics Collaborative: How to Design the Future of Health—Together

Watch All Webinars & Presentations>> | Read More on FDNA Insights>>

In The News

• The Boston Globe – Facial Recognition Zeros in on Genetic Disorders
• Jerusalem Post – From Facebook Facial Recognition to Genetic Disease Identification
• FierceBiotech – AI and Facial Diagnosis Company FDNA Sets Up Genomics Coalition
• Vogue – Why Our Faces are the New Social Currency
• Financial Times – Computer Vision: How Israel’s Secret Soldiers Drive its Tech Success
• Forrester – Augmented Intelligence Unlocks the Intelligence in AI
• Massachusetts Lawyers Weekly – AI in Healthcare: What You Need to Know
• LDV Capital – Nine Sectors Where Visual Technologies Will Improve Healthcare by 2028
• The Moneyball Medicine Podcast – Dekel Gelbman and How Machine Learning is Changing Rare Disease Diagnosis
• Electronic Health Report – Healthcare’s Most Pressing Problems, According to its Leaders (Part 3)
• Diagnostics World – What Facial Analysis Can Do for Rare Disease Diagnosis
• AI in Healthcare – Facial Recognition App Uses AI to Help ID Genetic Disorders
• Front Line Genomics – The Future of Phenotyping: What’s Next in AI
• SCOPE – Countdown to Big Data in Precision Health: Understanding the Hype and the Hope for AI in Health Care
• Leaps Magazine – This App Diagnoses Rare Genetic Disorders from a Picture

DeepGestalt In The News

• CNN – AI technology can identify genetic diseases by looking at your face, study says
• CBS – Could Artificial Intelligence Help Detect Rare Diseases Just By Looking At Faces?
• Nature – AI Face-Scanning App Spots Signs of Genetic Disorders
• The Economic Times – Click click snap: One look at the patient’s face, and AI can identify rare genetic disorders
• The Jerusalem Post – Facial Recognition Technology Highly Beneficial in Genetic Medicine
• Becker’s Hospital Review – An Algorithm Can Detect Genetic Conditions From Just a Photo
• Futurism – This AI Identifies Genetic Disorders by Looking at Face Shape
• Der Spiegel – Artificial intelligence recognizes rare hereditary diseases via the face
• La Repubblica – Experience the app that recognizes rare genetic diseases from pictures of the face

See All of FDNA In The News>>

Publications

• Gurovich Y, et. al. Identifying rare genetic syndromes using deep learning Nature Medicine
• Pantel JT, et. al. Advances in computer-assisted syndrome recognition by the example of inborn errors of metabolism J Inherit Metab Dis
• Martinez-Monseny A, et al. From gestalt to gene: early predictive dysmorphic features of PMM2-CDG J Med Genet
• Amudhavalli SM, et. al. Further delineation of Aymé‐Gripp syndrome and use of automated facial analysis tool Am J Med Genet
• Vorravanpreecha N, et. al. Studying Down syndrome recognition probabilities in Thai children with de‐identified computer‐aided facial analysis American Journal of Medical Genetics Am J Med Genet
• Jiang Y, et. al. The phenotypic spectrum of Xia‐Gibbs syndrome Am J Med Genet
• Ferreira, CR, et. al. Recognizable phenotypes in CDG J Inherit Metab Dis
• Zarate YA, et. al. Natural history and genotype-phenotype correlations in 72 individuals with SATB2-associated syndrome Am J Med Genet
• Knaus A, et. al.  Characterization of glycosylphosphatidylinositol biosynthesis defects by clinical features, flow cytometry, and automated image analysis Genome Med

See All Publications>>

Announcements

• FDNA Publishes Study in Nature Medicine Defining New Artificial Intelligence Standard in Healthcare Read More on Business wire>>
• FDNA Announces 100,000 Patients’ Lives Impacted Through Face2Gene Read More>>
• FDNA Expands Leadership Team Read More on Business Wire>>
• Send the phenotype to the lab with Face2Gene CLINIC Learn How>>

See All Announcements>>

The post 2018 Year in Review appeared first on FDNA™.

Advocacy: “Nobody needs to wait a single moment before starting to improve the world.”

Every month during the 2017 Year of Discovery, clinicians, labs and patients focused on a specific disease category to build a repository of rare disease “big data.” Sponsors including GeneDx and Blueprint Genetics helped drive patient case uploads by matching each case loaded with a charitable donation to patient advocacy charities. As a result of the increased community support, Face2Gene improved its recognition and understanding of the phenotype of dozens of diseases, including Sanfilippo Syndrome and a variety of craniosynostoses.

The Year of Discovery launched on 2017’s World Rare Disease Day. Look out for another exciting announcement during this year’s February 28 event.

Integrations: Better together

Across the globe, genetics labs including Ambry Genetics, GeneDx and Blueprint Genetics are integrating Face2Gene into their workflow. With the addition of these labs, over 70 percent of clinical geneticists worldwide are able to harness the power of artificial intelligence and computer vision to highlight genetic variants correlated with underlying diseases, increasing the diagnostic yield of genetic testing for their patients. Dramatically, we should say: preliminary results from the PEDIA study indicate adding phenotypic data and facial analysis can triple the diagnostic yield from genetic sequencing alone, in some cases.

We’re building relationships internally, too: in 2017, the FDNA Team grew by 23 people, full and part time, magnifying the human brain power behind the Face2Gene AI.

Product expansion: Suite, suite progress

These integrations are made possible by the latest additions to the Face2Gene suite. Genetics labs can use Face2Gene’s new LABS capability to securely transmit next-generation phenotyping and facial analysis insights directly into the molecular interpretation pipeline to increase diagnostic speed and accuracy.

Using the Face2Gene RESEARCH app, clinicians can use de-identified information to create cohorts and test hypotheses. Many abstracts and publications are resulting.

In the News: Our ears are burning

Artificial intelligence has been a hot topic in the news this year. Cygnis Media highlighted a range of ways machine learning and artificial intelligence are changing modern medicine, from personal trainers in biosensing earbuds to eye-tracking technology that can identity Autism Spectrum Disorders early. A special edition of TIME investigated advancements from smart-home thermostats to self-driving cars, and even how etiquette changes when we interact with machines.

FDNA found itself mentioned in dozens of high-profile articles, including the cover story of Fortune’s future issue, The Doctor Will See You Now, and the Economist’s September issue, What Machines Can Tell From Your Face. WIRED called Face2Gene “a breakthrough method… the most promising to deliver AI’s 50-year-old promise to revolutionize medicine.”

Partnerships: Left side, strong side

FDNA’s network of databases, researchers, and clinicians continued to grow this year. POSSUMWeb, a leading dysmorphology database, announced in October that it would partner with FDNA for integration and distribution of its over 40,000 images through Face2Gene LIBRARY. The Greenwood Genetic Center (GGC) announced its intention to analyze thousands of undiagnosed cases with Face2Gene, with the goal of finding new leads for unsolved cases. And at the end of 2017, Vanderbilt University Medical Center announced their use of Face2Gene as part of the NIH Undiagnosed Disease Network.

FDNA partnered with Cincinnati Children’s Hospital and used photos of patients with confirmed PACS1 diagnoses to train Face2Gene on disease-related features and as a result, the system reached 96 percent performance.

Future Plans: To boldly go

With all this momentum, FDNA is excited to launch a new effort to use FDNA’s artificial intelligence and deep learning technology to develop precision medicine approaches for diagnosing and treating disease. Details to come on World Rare Disease Day.

The post 2017 Year in Review appeared first on FDNA™.