International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
•
Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
Home
Research Paper
Submit Research Paper
Publication Guidelines
Publication Charges
Upload Documents
Track Status / Pay Fees / Download Publication Certi.
Editors & Reviewers
View All
Join as a Reviewer
Reviewer Referral Program
Get Membership Certificate
Current Issue
Publication Archive
Conference
Publishing Conf. with IJFMR
Upcoming Conference(s) ↓
WSMCDD-2025
GSMCDD-2025
Conferences Published ↓
RBS:RH-COVID-19 (2023)
ICMRS'23
PIPRDA-2023
Contact Us
Plagiarism is checked by the leading plagiarism checker
Call for Paper
Volume 6 Issue 5
September-October 2024
Indexing Partners
Artificial Intelligence in Biology
Author(s) | Anurag, Yashdeep Srivastava, Aniket Sharma, Dheerendra kumar, Sumit Pandey, Nishchal Maurya, Abhishek Gupta |
---|---|
Country | India |
Abstract | This article provides an in-depth analysis of the use of Artificial Intelligence (AI) in various aspects of biology, including healthcare, agriculture, and environmental monitoring. It highlights AI's ability to mimic human intelligence and analyze large datasets for predictions and tasks. The article also discusses its integration into Chinese medicine, where AI-guided diagnostic and therapeutic systems optimize clinical treatments and health management. AI is also used in disease management, analyzing data on diseases and pests, predicting their impact on ecosystems, and implementing preventative measures. The article also highlights the role of integrated information systems in environmental monitoring. Artificial intelligence (AI) has significant potential in healthcare research and chemical discoveries. Pharmaceutical companies are using AI to improve drug development by utilizing computational biology and machine learning systems to predict molecular behavior and the likelihood of finding a useful drug. This saves time and money on unnecessary tests. Clinical studies, electronic medical records, high-resolution medical images, and genomic profiles can be used as resources for drug development. Strong AI systems can analyze extensive data sets in pharmaceutical and medical research. This review focuses on integrating knowledge of cancer drugs, drug resistance, next-generation sequencing, genetic variants, and structural biology in cancer precision drug discovery. |
Keywords | AI in biosciences, biomedical, Agricultural engineering, Drug discovery, Molecular Diagnostics |
Field | Engineering |
Published In | Volume 6, Issue 2, March-April 2024 |
Published On | 2024-03-18 |
Cite This | Artificial Intelligence in Biology - Anurag, Yashdeep Srivastava, Aniket Sharma, Dheerendra kumar, Sumit Pandey, Nishchal Maurya, Abhishek Gupta - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.15067 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i02.15067 |
Short DOI | https://doi.org/gtnkc2 |
Share this
E-ISSN 2582-2160
doi
CrossRef DOI is assigned to each research paper published in our journal.
IJFMR DOI prefix is
10.36948/ijfmr
Downloads
All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.