Skip to main navigation
Skip to search
Skip to main content
College of Professional and Continuing Education Home
Search content at College of Professional and Continuing Education
Home
Profiles
Units
Projects
Publications
Prizes
Activities
Press/Media
AI in drug discovery and its clinical relevance
Rizwan Qureshi
, Muhammad Irfan
, Taimoor Muzaffar Gondal
,
Sheheryar Khan
, Jia Wu
, Muhammad Usman Hadi
, John Heymach
, Xiuning Le
, Hong Yan
, Tanvir Alam
Division of Science, Engineering and Health Studies (SEHS)
Research output
:
Contribution to journal
›
Review article
›
peer-review
201
Citations (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'AI in drug discovery and its clinical relevance'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Artificial Intelligence
100%
Clinical Significance
100%
Drug Discovery
100%
Drug pipeline
100%
Artificial Intelligence Techniques
66%
Drug Design
66%
COVID-19 Pandemic
33%
Deep Learning
33%
Artificial Intelligence Applications
33%
Cloud Computing
33%
Personal Health
33%
Molecular Dynamics Simulation
33%
Public Health Organizations
33%
Medical Data
33%
Data Complexity
33%
Medical Information
33%
Molecular Docking
33%
Start-up Companies
33%
Biotechnology Drugs
33%
Computational Approach
33%
Network Reinforcement
33%
Open Database
33%
Molecular Representation
33%
Graph Neural Network
33%
Substructure Method
33%
Drug Analysis
33%
Molecular Screening
33%
Data Disparity
33%
Computational Drug Discovery
33%
Dynamic Molecular
33%
Reinforcement Learning
33%
Clinical Setting
33%
Drug Response
33%
De-novo Design
33%
Neuroscience
Molecular Docking
100%
Neural Network
100%
Reinforcement Learning
100%
Biochemistry, Genetics and Molecular Biology
Artificial Intelligence
100%
Dynamics
16%
Hope
16%
De Novo Design
16%
Docking (Molecular)
16%
Drug Response
16%
Pharmacology, Toxicology and Pharmaceutical Science
Drug Discovery
100%
Drug Development
40%
Pandemic
20%