TY - JOUR
T1 - Face recognition in identifying genetic diseases
T2 - a progress review
AU - Aurellia, Salsabila
AU - Rahman, Siti Fauziyah
N1 - Funding Information:
We gratefully acknowledge the funding from Kementerian Pendidikan, Kebudayaan, Riset Dan Teknologi through Penelitian Tesis Magister 2022 No. NKB-1037/UN2.RST/HKP.05.00/2022.
Publisher Copyright:
© 2023, Institute of Advanced Engineering and Science. All rights reserved.
PY - 2023/9
Y1 - 2023/9
N2 - Genetic diseases vary widely. Practitioners often face the complexity of determining genetic diseases. In distinguishing one genetic disease from another, it is difficult to do without a thorough test on the patient or also known as genetic testing. However, in some previous studies, genetic diseases have unique physical characteristics in sufferers. This leads to detecting differences in these physical characteristics to assist doctors in diagnosing people with genetic diseases. In recent years, facial recognition research has been quite active. Researchers continue to develop it from various existing methods, algorithms, approaches, and databases where the application is applied in various fields, one of which is medical imagery. Face recognition is one of the options for identifying disease. The condition of a person's face can be said to be a representation of a person's health. Where the accuracy in early detection can be pretty good, so face recognition is also one of the solutions that can be used to identify various genetic diseases in collaboration with artificial intelligence. This article review will focus more on the development of facial recognition in 2-dimensional images, showing that different methods can produce different results and face recognition can also overcome complex genetic disease variations.
AB - Genetic diseases vary widely. Practitioners often face the complexity of determining genetic diseases. In distinguishing one genetic disease from another, it is difficult to do without a thorough test on the patient or also known as genetic testing. However, in some previous studies, genetic diseases have unique physical characteristics in sufferers. This leads to detecting differences in these physical characteristics to assist doctors in diagnosing people with genetic diseases. In recent years, facial recognition research has been quite active. Researchers continue to develop it from various existing methods, algorithms, approaches, and databases where the application is applied in various fields, one of which is medical imagery. Face recognition is one of the options for identifying disease. The condition of a person's face can be said to be a representation of a person's health. Where the accuracy in early detection can be pretty good, so face recognition is also one of the solutions that can be used to identify various genetic diseases in collaboration with artificial intelligence. This article review will focus more on the development of facial recognition in 2-dimensional images, showing that different methods can produce different results and face recognition can also overcome complex genetic disease variations.
KW - Face recognition
KW - 2-dimensional
KW - Artificial intelligence
KW - Genetic disease
KW - Identification
UR - http://www.scopus.com/inward/record.url?scp=85152946821&partnerID=8YFLogxK
U2 - 10.11591/ijai.v12.i3.pp1019-1025
DO - 10.11591/ijai.v12.i3.pp1019-1025
M3 - Article
AN - SCOPUS:85152946821
SN - 2089-4872
VL - 12
SP - 1019
EP - 1025
JO - IAES International Journal of Artificial Intelligence
JF - IAES International Journal of Artificial Intelligence
IS - 3
ER -