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Overall value:
93 pts
Face2Gene is free mobile app developed by FDNA, which uses Facial Dysmorphology Novel Analysis technology to analyze facial photos in order to detect any features and patterns that could be associated with genetic syndromes.

Scores

Cost-in-use
Free
100 pts
App Interface Usability
Modern, intuitive and easy-to-navigate interface; reaching for Support crashes the app
83 pts
Multimedia Usage
The app allows taking and uploading photos
95 pts
Real World Usability
The app is designed exclusively for healthcare providers
95 pts

There are genetic syndromes that can be identified visually, because of their recognizable facial patterns and features, such as Trisomy 21, better known as Down syndrome. But a lot of genetic syndromes simply can't be identified by facial characteristics, which may only display at a later age or never.

Early detection of these syndromes by identifying facial dysmorphic features and recognizable patterns of human malformations may be a key for their better understanding and for providing a better care and better quality of life to children with various genetic syndromes.

FDNA, which stands for Facial Dysmorphology Novel Analysis, is a Boston-based company with a mission to detect rare or difficult-to-diagnose genetic syndromes and to improve the quality of life of patients with these syndromes. FDNA technology uses facial photos to detect any features and patterns that could be associated with genetic syndromes.

The good news is that FDNA also released a free app for mobile devices that allows medical providers to take and upload the photos of their patients and have them analyzed and evaluated for specific facial features outside normal standard deviations and cross-referenced to a database of genetic conditions which these features may be associated to.

Speaking in geeky tech language this is how it works:
The app's deep learning algorithms first build syndrome-specific computational-based classifiers, called syndrome gestalts. Then, a proprietary technology converts uploaded patient photo into mathematical facial descriptors, i.e. patient's facial mesh, which is compared to syndrome gestalts to quantify similarity or gestalt scores in order to get a prioritized list of syndromes having a similar morphology. Finally, artificial intelligence suggests likely phenotypic traits in order to annotate features and prioritize syndromes.

Speaking in simpler language, just upload the patient's photo and get a suggestion on which syndrome it may be.
The app requires you to log in, or to create account, before you can use it. It will ask for your name, email, password, along with your credentials and geographic location.

Once you get inside, you'll see a simple home screen offering you to create a new case automatically by selecting one of the starting points. You may take new photo using phone camera, browse existing photos or select from list of physical and physiological features that may be associated with genetic disorders, for example syndactyly, various abnormalities, etc. This list is huge, but there's a Search option that makes browsing easier, if you know what you're looking for. Still, it would be better if the features are sorted by sections or categories for easier navigation and finding the wanted features with less hassle. 

But, the Face2Gene is mainly an app relying on taking and analyzing photos and it does that in a really impressive way. Either you take the photo or upload one from phone gallery; both ways are simple and fast. The analyze starts immediately, allowing you to add patient's name or ID, gender and age.

For the purpose of this review, we've created two cases. The first was a 4 year-old girl with Down syndrome and the second was a 2 year-old boy with suspected Catel-Manzke (CATMANS) syndrome.

While the first case was more obvious due to recognizable facial features related to Trisomy 21, another case was a bit tricky, because some features of Catel-Manzke syndrome may be common for other disorders as well.

Once the analysis is done, you'll see the results showing a list of 30 suggested syndromes, with face features and gestalt result (med, low or high) beside each. Impressively, we got accurate results for both cases. First has shown medium, almost high gestalt result for Down syndrome, while the second case was in low Med bar of gestalt results for Catel-Manzke syndrome. Results can be refined by setting the inheritance mode or visible features.

Tapping on the syndrome allows you to compare image of your patient with the image provided by the app (with the heat map on or off), to add features typical for the syndrome that are manifested in your patient, or to find out more about the syndrome, which provides exhaustive and well-referenced info (although without links), but not for all syndromes (there was no info available for Catel-Mantzke syndrome), which is really disappointing. Here, on the case screen you can also set a diagnosis for a case (differential, clinical or molecular), which will move the syndrome into selected slot.

Case screen also offer couple of more options, such as case overview, seeing all photos (cases can have multiple photos), adding physical measures and viewing and editing general info about your patient.

There's not much info about the FDNA company, or its mission. There is Support option which unfortunately crashes the app and after several attempts to open this option, the app wouldn't start at all. When we finally managed to open it again, the Support option was still unavailable. The support is available before you register or log in tho, but once you enter the app there's no option to contact the support.

These are obviously some tweaks for future updates that should be addressed to developers, but overall, Face2Gene app is very useful, if not a must-have tool for all healthcare providers dealing with complex genetic syndromes.

Benefit: Clinicians in pediatrics setting, who see a fair number of genetically-linked conditions, may find this app useful.

Verdict:

For
  • Easy-to-use interface
  • Impressive accuracy when analyzing photos and detecting the syndromes
  • A lot of options for fine tuning the cases
Against
  • Not each syndrome has information available
  • No external reference links or info about company
  • Support option crashes the app

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