AI Image Analysis to Expedite the Diagnosis of Developmental and Genetic Disorders
Used in more than 10,000 medical centers worldwide
Over 100 peer-reviewed publications and articles
AI-Powered diagnosis support & care management tools
Enabling Early Detection of Developmental Delays, Genetic Disorders, and Rare Diseases
- FDNA empowers parents, school nurses, and pediatric specialists to flag potential developmental, neurological, and genetic conditions, and connect with the right specialists, as early as possible.
- We offer a digital front door for healthcare providers, decision support tools for diagnosis, and care management tools for therapy.
- Our data clearing house offers streamlined interoperability between healthcare providers, patients, and the pharmaceutical industry, including therapy services and contract research organizations (CROs).
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cases analyzed with
our technology
cases in the
last 3 months
cases in the
last 30 days
HOSPITALS, CLINICS
AND ORGANIZATIONS
Empowering Parents, Providers & Pharma Companies
Connecting Concerned Parents & Patients with Healthcare Providers, Pharma & CROs
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10,000+ Medical Centers, Clinics and Hospitals
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From early signs to treatment plans
Supporting the Patient’s Journey Every Step of the Way
Our impact across the world
FDNA’s Technology is Used in Over 130 Countries Worldwide
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Our technology
AI-Powered Image Analysis & Risk Assessment
As the world leader in AI-powered image analysis to aid in diagnosing developmental & genetic disorders, and rare diseases, FDNA develops the most comprehensive database of relevant phenotypic information, crowdsourced from clinicians, patients, labs, and researchers. This real-world data, along with FDNA’s technologies, help expedite diagnosis and reduce the cost of care.
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FDNA’s Multi-Modal Algorithm Framework
FDNA builds a trusted AI framework by integrating various algorithms and cross-referencing outcomes from multiple input modalities, such as image analysis, symptom assessment, natural language processing (NLP), video analysis, and voice analysis, we can achieve a heightened capability in detecting health signals and more robustly cross-validate identified health conditions.
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Learn More About FDNA’s Multi-Modal Algorithm Frameworks
- Deep Gestalt®: An algorithm that maps images to potential syndromes.
- Gestalt Matcher™: An algorithm to discover new or rare syndromes, and for patient matching.
- Feature Extraction Algorithm: An algorithm that searches for facial characteristics using images and maps these characteristics to HPO terms.
- Heat Maps: Provides clinicians with intuitive, visual references for why the Deep Gestalt algorithm matched certain results.
- Focus Assessment: Guides the user through a post-image analysis assessment when the AI produces two or more high-confidence results. The assessment is utilized to diminish ambiguity between syndromes that exhibit similar dysmorphic signals.
- Feature Match™: Algorithm utilizing HPOs and syndrome atrophy models, mapped to numerical vectors and syndrome-to-HPO probability score.
- Clinical Notes Analyzer: An NLP algorithm designed to extract HPOs, biomarkers, and symptoms from health records and clinical notes. It supports both text and voice input.
- Symptom Assessment: Guides parents through an assessment of their child’s condition, behaviors, symptoms, and physical features and provides content and suggestions for specialist referrals. The assessment uses a statistical matching algorithm between the detected symptoms and potential health conditions.
- D-Score™: An algorithm that determines face dysmorphology in an image.
- A-Score™: An algorithm that seeks to identify facial characteristics in autistic syndromic and non-syndromic children. Syndromic children: with a diagnosed genetic condition with specific facial dysmorphology. Non-syndromic: no genetic condition described.
As reviewed by
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