Deep Learning Analysis of Virtual Reality Technology for pharma industry

The use of virtual reality (VR) technology is rapidly expanding in the pharmaceutical industry, and with the application of deep learning analysis, this technology is becoming more sophisticated and effective. Deep learning is a subfield of artificial intelligence that enables machines to learn and...

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Bibliographic Details
Published inJournal of commercial biotechnology Vol. 27; no. 4; pp. 169 - 175
Main Authors Gu, Qiulin, Zhang, Li
Format Journal Article
LanguageEnglish
Published London thinkBiotech LLC 15.02.2023
Subjects
Algorithms
Artificial intelligence
Computer applications
Deep learning
Drug development
Drug discovery
Learning algorithms
Medical personnel
Pharmaceutical industry
Precision medicine
Virtual reality
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Summary:The use of virtual reality (VR) technology is rapidly expanding in the pharmaceutical industry, and with the application of deep learning analysis, this technology is becoming more sophisticated and effective. Deep learning is a subfield of artificial intelligence that enables machines to learn and improve through experience, and its application in VR technology has the potential to transform the way pharmaceutical research and development is conducted. The use of VR technology in the pharmaceutical industry has numerous applications, including drug discovery, development, and testing. VR technology allows for the simulation of complex biological processes, which can lead to more accurate and efficient drug development. Additionally, VR technology can be used to train medical professionals, provide patient education, and improve the overall delivery of care. Deep learning analysis of VR technology in the pharmaceutical industry has the potential to unlock new insights and improve the efficiency of drug discovery and development. With the application of deep learning algorithms, machines can learn from large datasets and simulate complex biological processes with greater accuracy and speed. This can help to identify potential drug candidates more efficiently, reducing the time and costs associated with traditional drug development processes. Furthermore, deep learning analysis of VR technology can also be used to improve patient outcomes by enabling more personalized medicine. By analyzing large amounts of patient data, deep learning algorithms can help identify the best treatments for individual patients, leading to better health outcomes
ISSN:1462-8732
1478-565X
DOI:10.5912/jcb1323