Author(s):
Goli Venkateshwarlu, Kimmi Katoch, Nikita, Kapil Maurya
Email(s):
katochkimmi@gmail.com
DOI:
10.52711/2349-2988.2026.00053 
Address:
Goli Venkateshwarlu, Kimmi Katoch, Nikita, Kapil Maurya
Arni School of Pharmacy, Arni University, Kathgarh, Indora, Kangra -176401, Himachal Pradesh, India.
*Corresponding Author
Published In:
Volume - 18,
Issue - 4,
Year - 2026
ABSTRACT:
Artificial intelligence entails a broad spectrum of computational techniques and algorithms, which can be divided into several key groups based on their core concepts and approaches. All humans share the same base set of genes, but health genes are unmutated versions that produce normal, healthy proteins to keep the body functioning. Disease genes carry harmful mutations or variants that produce abnormal proteins or none at all which triggers health conditions. When discussing AI in oncology, AI accelerates precision oncology by rapidly analyzing massive genomic data sets to identify mutations, predict therapeutic vulnerabilities and map complex pathways. Cutting-edge models can predict the genetic activity of thousands of genes (such as EGFR or KRAS) using only standard microscopy images, bypassing time-consuming genetic sequencing. Cancer care generates vast and heterogeneous datasets spanning radiology, pathology, genomics, clinical records.
Cite this article:
Goli Venkateshwarlu, Kimmi Katoch, Nikita, Kapil Maurya. AI Role in Oncogene Sequence Identification and Analysis of Healthy and Diseased patient. Research Journal of Science and Technology. 2026; 18(4):381-3. doi: 10.52711/2349-2988.2026.00053
Cite(Electronic):
Goli Venkateshwarlu, Kimmi Katoch, Nikita, Kapil Maurya. AI Role in Oncogene Sequence Identification and Analysis of Healthy and Diseased patient. Research Journal of Science and Technology. 2026; 18(4):381-3. doi: 10.52711/2349-2988.2026.00053 Available on: https://www.rjstonline.com/AbstractView.aspx?PID=2026-18-4-9
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