Title
Artificial intelligence in Immuno-genetics
Authors
Raed Farzan1,2,3,*
Affiliation
1Department of Clinical Laboratory Sciences, College of Applied Medical Scienecs, King Saud University, Riyadh - 11433, Saudi Arabia; 2Center of Excellence in Biotechnology Research, King Saud University, Riyadh - 11433, Saudi Arabia; 3Medical and Molecular Genetics Research, King Saud University, Riyadh-11433, Saudi Arabia
Email: rfarzan@ksu.edu.sa; cls@ksu.edu.sa
Article Type
Review
Date
Received January 1, 2024; Revised January 31, 2024; Accepted January 31, 2024, Published January 31, 2024
Abstract
Rapid advancements in the field of artificial intelligence (AI) have opened up unprecedented opportunities to revolutionize various scientific domains, including immunology and genetics. Therefore, it is of interest to explore the emerging applications of AI in immunology and genetics, with the objective of enhancing our understanding of the dynamic intricacies of the immune system, disease etiology, and genetic variations. Hence, the use of AI methodologies in immunological and genetic datasets, thereby facilitating the development of innovative approaches in the realms of diagnosis, treatment, and personalized medicine is reviewed.
Keywords
Artificial intelligence; immunology; genetics; machine learning; deep learning.
Citation
Farzan, Bioinformation 20(1): 29-35 (2024)
Edited by
P Kangueane
ISSN
0973-2063
Publisher
License
This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.
