FDNA, MCRI Partner to Improve Speed, Accuracy of Rare Disease Diagnosis

October 11, 2017
GenomeWeb 
“Boston-based FDNA has partnered with Murdoch Children’s Research Institution (MCRI) and the Victorian Clinical Genetics Service to integrate and exclusively distribute MCRI’s POSSUM web database through FDNA’s Face2Gene software. POSSUM web’s database contains 30,000 images, including photos, x-rays, scans, and diagrams. To identify genetic syndromes, FDNA’s Face2Gene software combines facial analysis with other phenotypic traits and variants from genetic tests, such as exome and genome sequencing. The database integration will enable clinicians to diagnose patients more quickly by providing information for more than 4,000 genetic syndromes, including multiple malformations, metabolic, teratogenic, chromosomal, and skeletal syndromes.”

The article describes how FDNA and the Murdoch Children’s Research Institute (MCRI) have partnered to enhance the diagnosis of rare diseases, emphasizing improved speed and accuracy. Integrating FDNA’s advanced AI technology with MCRI’s clinical expertise aims to streamline the identification of genetic disorders. This joint effort leverages FDNA’s Face2Gene platform, which uses facial analysis and deep learning to detect phenotypic markers of rare diseases. The partnership seeks to reduce diagnostic timelines and increase precision, benefiting patients with rare conditions by providing quicker, more accurate diagnoses and facilitating tailored treatment plans.

Related articles

Dr. Bruno

The Importance of Teaching Face2Gene to Pediatricians

In the world of rare genetic diseases, early diagnosis is often the key to better patient outcomes. However, the diagnostic journey can be long and complex, sometimes taking years before a definitive answer is found. Dr. Bruno Bordest, a Brazilian geneticist who teaches at the Universidade Federal de Mato Grosso, has been working to bridge […]

Continue reading
AI in genetic diagnosis

The Evolution of FDNA’s technology: An Interview with Aviram Bar Haim

Analyzing facial features has long been a vital step in diagnosing genetic syndromes. In recent years, AI-driven technologies have transformed this process, making it more efficient and accurate. Leading this innovation is Face2Gene, an advanced AI platform that leverages machine learning to assist clinicians in identifying genetic disorders. To explore the development of this groundbreaking […]

Continue reading