Researchers at the University of Bonn show that using portrait photos in combination with genetic and patient data improves diagnoses
Every year, around half a million children worldwide are born with a rare hereditary disease. Obtaining a definitive diagnosis can be difficult and time consuming. In a study of 679 patients with 105 different rare diseases, scientists from the University of Bonn and the Charité – Universitätsmedizin Berlin have shown that artificial intelligence can be used to diagnose rare diseases more efficiently and reliably. A neural network automatically combines portrait photos with genetic and patient data. The results are now presented in the journal “Genetics in Medicine”.
Many patients with rare diseases go through lengthy trials and tribulations until they are correctly diagnosed. “This results in a loss of valuable time that is actually needed for early therapy in order to avert progressive damage,” explains Prof. Dr. med. Dipl. Phys. Peter Krawitz from the Institute for Genomic Statistics and Bioinformatics at the University Hospital Bonn (UKB). Together with an international team of researchers, he demonstrates how artificial intelligence can be used to make comparatively quick and reliable diagnoses in facial analysis.
The researchers used data of 679 patients with 105 different diseases caused by the change in a single gene. These include, for example, mucopolysaccharidosis (MPS), which leads to bone deformation, learning difficulties and stunted growth. Mabry syndrome also results in intellectual disability. All these diseases have in common that the facial features of those affected show abnormalities. This is particularly characteristic, for example, of Kabuki syndrome, which is reminiscent of the make-up of a traditional Japanese form of theatre. The eyebrows are arched, the eye-distance is wide and the spaces between the eyelids are long.
The used software can automatically detect these characteristic features from a photo. Together with the clinical symptoms of the patients and genetic data, it is possible to calculate with high accuracy which disease is most likely to be involved. The AI and digital health company FDNA has developed the neural network DeepGestalt, which the researchers use as a tool of artificial intelligence for their study. “PEDIA is a unique example of next-generation phenotyping technologies,” said Dekel Gelbman, CEO of FDNA. “Integrating an advanced AI and facial analysis framework such as DeepGestalt into the variant analysis workflow will result in a new paradigm for superior genetic testing”.
Researchers train the neural network with 30,000 images
The scientists trained this computer program with around 30,000 portrait pictures of people affected by rare syndromal diseases. “In combination with facial analysis, it is possible to filter out the decisive genetic factors and prioritize genes,” says Krawitz. “Merging data in the neuronal network reduces data analysis time and leads to a higher rate of diagnosis.”
The head of the Institute of Genomic Statistics and Bioinformatics at the UKB has been working with FDNA for some time. “This is of great scientific interest to us and also enables us to find a cause in some unsolved cases,” said Krawitz. Many patients are currently still looking for an explanation for their symptoms.
The study is a team effort between computer science and medicine. This can also be seen in the shared first authorship of the computer scientist Tzung-Chien Hsieh, doctoral student at the institute of Professor Krawitz, and Dr. Martin Atta Mensah, physician at the Institute of Medical Genetics and Human Genetics of the Charité and Fellow of the Clinician Scientist Program of the Charité and Berlin Institute of Health (BIH). Prof. Dr. Stefan Mundlos, Director of the Institute of Medical Genetics and Human Genetics at the Charité, also participated in the study, as did over 90 other scientists.
“Patients want a prompt and accurate diagnosis. Artificial intelligence supports physicians and scientists in shortening the journey,” says Dr. Christine Mundlos, Deputy Managing Director of the alliance of patients with chronic rare diseases (ACHSE) e.V. “This also improves the quality of life of those affected to some extent.”
The Latest on: AI and facial analysis framework
via Google News
The Latest on: AI and facial analysis framework
- Xdroid Applauded by Frost & Sullivan for Its Innovative Voice and Facial Analytics Solution Portfolioon January 12, 2021 at 6:11 am
Based on its recent analysis of the European voice and facial analytics market, Frost & Sullivan recognizes Xdroid Voice Analytics with ...
- CES 2021 Taiwan startup GenkiTek designs and develops AI cameras and AI networking video recorderson January 12, 2021 at 4:09 am
GenkiTek, a spinoff company from Taiwan's Industrial Technology Research Institute designs and develops AI cameras and AI networking ...
- From facial recognition, to predictive technologies, big data policing is rife with technical, ethical and political landmineson January 12, 2021 at 2:17 am
Analysts have identified an impressive list of problems, from biased, incomplete or inaccurate data, opaque technology, erroneous predictions, lack ...
- Leading Facial Recognition Technology Provider Corsight AI Appoints Former UK Surveillance Camera Commissioner Tony Porter as Chief Privacy Officeron January 12, 2021 at 1:20 am
Corsight AI, a leading facial recognition solution provider, announced today the appointment of the UK's former Surveillance Camera Commissioner Tony Porter as its Chief Privacy Officer. Effective ...
- Former Surveillance Camera Commissioner Tony Porter to join facial recognition tech provider Corsight AIon January 12, 2021 at 1:03 am
The former Surveillance Camera Commissioner for England and Wales, Tony Porter, has been announced as Chief Privacy Officer for Corsight AI.
- The US Army is developing a nightmarish thermal facial recognition systemon January 11, 2021 at 3:09 pm
The US Army just took a giant step toward developing killer robots that can see and identify faces in the dark. DEVCOM, the US Army’s corporate research department, last week published a pre-print ...
- Capitol attack: FBI mum on facial recognition, Clearview AI searches spikeon January 11, 2021 at 10:44 am
BLM protesters were subject to surveillance, but feds aren't saying whether they're using the same tools to investigate riots ...
- Clearview AI biometrics searches spike as police work to identify Capitol rioterson January 11, 2021 at 8:52 am
U.S. law enforcement is using Clearview AI’s controversial facial recognition software to identify people who were present or took part in the Capitol riots.
- AnyVision Offers 5 Indications for Fair, Ethical and Unbiased Use of Face Recognition Amidst Rising Public Debateon January 8, 2021 at 8:30 am
AnyVision, a global leader in visual AI software, participated in the "Facial Recognition: Challenges and Solutions" conference hosted by Fordham University Law School last ...
- Facial Recognition Market by Size, Growth, Opportunity and Forecast to 2026on January 4, 2021 at 9:43 pm
Selbyville, Delaware According to the recent study titled 'Facial Recognition Market Size By Component, By Application, By End-Use, Industry Analysis Report, Regional Outlook, Growth Potential, ...
via Bing News