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Diagnosis from facial features

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Objective: Facial changes are common among nearly all acromegalic patients. As they develop slowly, patients often fail to notice such changes before they become obvious. Consequently, diagnosis and treatment are often delayed. So far, convenient and accurate early detection of this disease is still unavailable. This study is designed to combine the use of 3D imaging and machine learning techniques in facial feature analysis and identification of acromegalic patients, in an effort to ascertain how both techniques performed in terms of applicability and value in the early detection of the disease.
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Scanning the future of facial recognition

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AI face-scanning app spots signs of rare genetic disorders

Face2Gene is a suite of phenotyping applications that facilitate comprehensive and precise genetic evaluations. Learn More. 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. 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. Having an archive of cases easily accessible from my mobile device anytime and anywhere is a long-time unmet need. FDNA's solution is a huge leap forward for dysmorphology.
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AI face-scanning app spots signs of rare genetic disorders

At Tufts Medical Center we have been using this technology with some of our patients for about 2 and a half years. We are working to integrate it into the evaluation of every pediatric patient seen in our Genetics department. It has helped us make diagnoses in several cases. It also makes for seamless communication with a genetic testing laboratory.
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Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Researchers are improving the ability of algorithms to help spot the physical characteristics of conditions such as Cornelia de Lange syndrome.
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    Mazurg4 months ago

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