A study prepared by FDNA, a leader in the field of AI, in addition to providing early diagnosis, points out that the use of automatic facial analysis in the detection of genetic disorders adds to the importance of personal attention, which will contribute to improving the quality of life of the patient.
The research focuses on the use of a deep learning algorithm that uses and connects more than 17,000 facial images of patients diagnosed with hundreds of genetic syndromes.
Face technology analyzes, structures and analyzes the complex physiological properties of a person and then stores them in a database of more than 150,000 patients.
Given the high number of possible gene disorders, finding the right diagnosis remains a challenge for doctors, the authors said in a press release.
However, the technical director of FDNA Yaron Gurovich emphasized that the results of the study "open the door to future research and applications, as well as identify new genetic syndromes."
The data used in this study were taken from a platform promoted by the Face2Gene community, in which various physicians loaded facial images of more than 200 patients.
The AI suggested possible possible syndromes for each picture, and in most cases the researchers found that they corresponded to a clinical diagnosis.