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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM36303
Volume:
8 |
7 |
Jul 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Our project aims to confront the persistent challenge of developing effective cancer treatments, especially in light of drug resistance. n the quest for improved therapeutic outcomes, clinicians often resort to combining drugs, yet the task of selecting the optimal mix remains daunting. Herein lies our innovative proposal – Quantum Neural Networks (QNNs). By harnessing the computational prowess inherent in QNNs, we aim to unravel the intricate complexities of genetic data, thereby pinpointing elusive yet promising drug interactions that traditional methodologies may overlook.Through this ambitious endeavor, our aim is to expedite the drug discovery process and to tailor treatments to the unique genetic profiles of individual patients. In forging this path, our project not only promises hope in the ongoing battle against cancer but also represents a monumental leap forward in the realm of personalized medicine
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Publication Date
5/6/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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